Overview

Dataset statistics

Number of variables45
Number of observations37012
Missing cells186083
Missing cells (%)11.2%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory12.7 MiB
Average record size in memory360.0 B

Variable types

Categorical13
DateTime3
Numeric25
Boolean4

Warnings

Dataset has 2 (< 0.1%) duplicate rows Duplicates
name has a high cardinality: 35912 distinct values High cardinality
description has a high cardinality: 33912 distinct values High cardinality
neighborhood_overview has a high cardinality: 19385 distinct values High cardinality
host_about has a high cardinality: 15481 distinct values High cardinality
host_verifications has a high cardinality: 524 distinct values High cardinality
neighbourhood_cleansed has a high cardinality: 220 distinct values High cardinality
property_type has a high cardinality: 75 distinct values High cardinality
amenities has a high cardinality: 31671 distinct values High cardinality
availability_30 is highly correlated with availability_60 and 1 other fieldsHigh correlation
availability_60 is highly correlated with availability_30 and 1 other fieldsHigh correlation
availability_90 is highly correlated with availability_30 and 1 other fieldsHigh correlation
room_type is highly correlated with property_typeHigh correlation
property_type is highly correlated with room_typeHigh correlation
description has 1223 (3.3%) missing values Missing
neighborhood_overview has 13683 (37.0%) missing values Missing
host_about has 14844 (40.1%) missing values Missing
host_response_time has 18507 (50.0%) missing values Missing
host_response_rate has 18507 (50.0%) missing values Missing
host_acceptance_rate has 14633 (39.5%) missing values Missing
bedrooms has 3608 (9.7%) missing values Missing
beds has 490 (1.3%) missing values Missing
first_review has 9523 (25.7%) missing values Missing
last_review has 9523 (25.7%) missing values Missing
review_scores_rating has 10235 (27.7%) missing values Missing
review_scores_accuracy has 10259 (27.7%) missing values Missing
review_scores_cleanliness has 10248 (27.7%) missing values Missing
review_scores_checkin has 10271 (27.8%) missing values Missing
review_scores_communication has 10257 (27.7%) missing values Missing
review_scores_location has 10272 (27.8%) missing values Missing
review_scores_value has 10272 (27.8%) missing values Missing
reviews_per_month has 9523 (25.7%) missing values Missing
price is highly skewed (γ1 = 21.2915869) Skewed
maximum_nights is highly skewed (γ1 = 192.3352933) Skewed
name is uniformly distributed Uniform
description is uniformly distributed Uniform
host_response_rate has 930 (2.5%) zeros Zeros
host_acceptance_rate has 1401 (3.8%) zeros Zeros
host_total_listings_count has 4501 (12.2%) zeros Zeros
beds has 1391 (3.8%) zeros Zeros
availability_30 has 19305 (52.2%) zeros Zeros
availability_60 has 17604 (47.6%) zeros Zeros
availability_90 has 16770 (45.3%) zeros Zeros
availability_365 has 15121 (40.9%) zeros Zeros
number_of_reviews has 9523 (25.7%) zeros Zeros
number_of_reviews_ltm has 23720 (64.1%) zeros Zeros

Reproduction

Analysis started2021-04-13 03:30:33.107999
Analysis finished2021-04-13 03:32:39.720172
Duration2 minutes and 6.61 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

last_scraped
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
2021-02-05
24361 
2021-02-06
9882 
2021-02-04
2769 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters370120
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-05
2nd row2021-02-05
3rd row2021-02-05
4th row2021-02-05
5th row2021-02-06
ValueCountFrequency (%)
2021-02-0524361
65.8%
2021-02-069882
26.7%
2021-02-042769
 
7.5%
2021-04-12T21:32:39.950160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-04-12T21:32:40.032379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-0524361
65.8%
2021-02-069882
26.7%
2021-02-042769
 
7.5%

Most occurring characters

ValueCountFrequency (%)
2111036
30.0%
0111036
30.0%
-74024
20.0%
137012
 
10.0%
524361
 
6.6%
69882
 
2.7%
42769
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number296096
80.0%
Dash Punctuation74024
 
20.0%

Most frequent character per category

ValueCountFrequency (%)
2111036
37.5%
0111036
37.5%
137012
 
12.5%
524361
 
8.2%
69882
 
3.3%
42769
 
0.9%
ValueCountFrequency (%)
-74024
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common370120
100.0%

Most frequent character per script

ValueCountFrequency (%)
2111036
30.0%
0111036
30.0%
-74024
20.0%
137012
 
10.0%
524361
 
6.6%
69882
 
2.7%
42769
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII370120
100.0%

Most frequent character per block

ValueCountFrequency (%)
2111036
30.0%
0111036
30.0%
-74024
20.0%
137012
 
10.0%
524361
 
6.6%
69882
 
2.7%
42769
 
0.7%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct35912
Distinct (%)97.1%
Missing13
Missing (%)< 0.1%
Memory size289.3 KiB
Well-kept apartment home | 1BR in New York
 
37
Home away from home
 
17
Studio Loft
 
15
Cozy neighborhood Subway M/R<2min> & 7 Line<5min>
 
13
Beautiful 2 Double Bed Hotel Room
 
13
Other values (35907)
36904 

Length

Max length161
Median length38
Mean length37.37917241
Min length1

Characters and Unicode

Total characters1382992
Distinct characters741
Distinct categories21 ?
Distinct scripts11 ?
Distinct blocks23 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35284 ?
Unique (%)95.4%

Sample

1st rowSkylit Midtown Castle
2nd rowWhole flr w/private bdrm, bath & kitchen(pls read)
3rd rowBlissArtsSpace!
4th rowLarge Furnished Room Near B'way 
5th rowCozy Clean Guest Room - Family Apt
ValueCountFrequency (%)
Well-kept apartment home | 1BR in New York37
 
0.1%
Home away from home17
 
< 0.1%
Studio Loft15
 
< 0.1%
Cozy neighborhood Subway M/R<2min> & 7 Line<5min>13
 
< 0.1%
Beautiful 2 Double Bed Hotel Room13
 
< 0.1%
Beautiful King Bed Hotel Room13
 
< 0.1%
New york Multi-unit building12
 
< 0.1%
Easy access to Manhattan : Nice Condition room12
 
< 0.1%
Water View King Bed Hotel Room12
 
< 0.1%
Individual Cubicle Room in NYC/not shared/just you12
 
< 0.1%
Other values (35902)36843
99.5%
(Missing)13
 
< 0.1%
2021-04-12T21:32:40.439224image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
in12509
 
5.5%
room7707
 
3.4%
6267
 
2.7%
bedroom5567
 
2.4%
private5452
 
2.4%
apartment5115
 
2.2%
cozy3530
 
1.5%
apt3366
 
1.5%
studio3095
 
1.4%
the2986
 
1.3%
Other values (10624)172950
75.7%

Most occurring characters

ValueCountFrequency (%)
192881
 
13.9%
e97893
 
7.1%
o93920
 
6.8%
t81194
 
5.9%
a79950
 
5.8%
r74729
 
5.4%
i73879
 
5.3%
n73286
 
5.3%
l40557
 
2.9%
m37603
 
2.7%
Other values (731)537100
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter933169
67.5%
Uppercase Letter198909
 
14.4%
Space Separator192894
 
13.9%
Other Punctuation25815
 
1.9%
Decimal Number19533
 
1.4%
Dash Punctuation5135
 
0.4%
Math Symbol2164
 
0.2%
Other Letter1706
 
0.1%
Close Punctuation1149
 
0.1%
Open Punctuation1091
 
0.1%
Other values (11)1427
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
65
 
3.8%
36
 
2.1%
32
 
1.9%
32
 
1.9%
31
 
1.8%
30
 
1.8%
29
 
1.7%
26
 
1.5%
23
 
1.3%
22
 
1.3%
Other values (413)1380
80.9%
ValueCountFrequency (%)
238
28.0%
103
12.1%
93
 
10.9%
34
 
4.0%
32
 
3.8%
29
 
3.4%
29
 
3.4%
🌟18
 
2.1%
18
 
2.1%
14
 
1.6%
Other values (101)243
28.6%
ValueCountFrequency (%)
e97893
10.5%
o93920
 
10.1%
t81194
 
8.7%
a79950
 
8.6%
r74729
 
8.0%
i73879
 
7.9%
n73286
 
7.9%
l40557
 
4.3%
m37603
 
4.0%
s37243
 
4.0%
Other values (55)242915
26.0%
ValueCountFrequency (%)
B22212
 
11.2%
S19173
 
9.6%
C15476
 
7.8%
A14123
 
7.1%
R13296
 
6.7%
P11205
 
5.6%
L10159
 
5.1%
E9807
 
4.9%
M8952
 
4.5%
N8650
 
4.3%
Other values (41)65856
33.1%
ValueCountFrequency (%)
,7253
28.1%
!5231
20.3%
/4264
16.5%
.3489
13.5%
&2583
 
10.0%
'828
 
3.2%
*625
 
2.4%
:478
 
1.9%
#432
 
1.7%
"234
 
0.9%
Other values (14)398
 
1.5%
ValueCountFrequency (%)
16322
32.4%
25433
27.8%
32015
 
10.3%
01780
 
9.1%
51605
 
8.2%
41053
 
5.4%
6384
 
2.0%
7365
 
1.9%
8332
 
1.7%
9239
 
1.2%
Other values (4)5
 
< 0.1%
ValueCountFrequency (%)
+888
41.0%
|724
33.5%
~343
 
15.9%
=80
 
3.7%
>68
 
3.1%
<42
 
1.9%
13
 
0.6%
3
 
0.1%
2
 
0.1%
1
 
< 0.1%
ValueCountFrequency (%)
´4
26.7%
^4
26.7%
🏼2
13.3%
🏽2
13.3%
`1
 
6.7%
🏾1
 
6.7%
🏻1
 
6.7%
ValueCountFrequency (%)
(1035
94.9%
[27
 
2.5%
23
 
2.1%
3
 
0.3%
2
 
0.2%
{1
 
0.1%
ValueCountFrequency (%)
)1092
95.0%
]27
 
2.3%
24
 
2.1%
3
 
0.3%
2
 
0.2%
}1
 
0.1%
ValueCountFrequency (%)
-5073
98.8%
35
 
0.7%
25
 
0.5%
1
 
< 0.1%
1
 
< 0.1%
ValueCountFrequency (%)
135
84.4%
22
 
13.8%
͠2
 
1.2%
͜1
 
0.6%
ValueCountFrequency (%)
192881
> 99.9%
 7
 
< 0.1%
 6
 
< 0.1%
ValueCountFrequency (%)
201
83.4%
40
 
16.6%
ValueCountFrequency (%)
34
81.0%
8
 
19.0%
ValueCountFrequency (%)
²6
85.7%
½1
 
14.3%
ValueCountFrequency (%)
2
66.7%
1
33.3%
ValueCountFrequency (%)
$73
100.0%
ValueCountFrequency (%)
_27
100.0%
ValueCountFrequency (%)
7
100.0%
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1131888
81.8%
Common249047
 
18.0%
Han1498
 
0.1%
Cyrillic190
 
< 0.1%
Inherited161
 
< 0.1%
Katakana115
 
< 0.1%
Hiragana53
 
< 0.1%
Hebrew19
 
< 0.1%
Hangul19
 
< 0.1%
Thai1
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
65
 
4.3%
36
 
2.4%
32
 
2.1%
32
 
2.1%
31
 
2.1%
30
 
2.0%
29
 
1.9%
26
 
1.7%
23
 
1.5%
22
 
1.5%
Other values (331)1172
78.2%
ValueCountFrequency (%)
192881
77.4%
,7253
 
2.9%
16322
 
2.5%
25433
 
2.2%
!5231
 
2.1%
-5073
 
2.0%
/4264
 
1.7%
.3489
 
1.4%
&2583
 
1.0%
32015
 
0.8%
Other values (187)14503
 
5.8%
ValueCountFrequency (%)
e97893
 
8.6%
o93920
 
8.3%
t81194
 
7.2%
a79950
 
7.1%
r74729
 
6.6%
i73879
 
6.5%
n73286
 
6.5%
l40557
 
3.6%
m37603
 
3.3%
s37243
 
3.3%
Other values (64)441634
39.0%
ValueCountFrequency (%)
а24
 
12.6%
т14
 
7.4%
н14
 
7.4%
о11
 
5.8%
р11
 
5.8%
е10
 
5.3%
к8
 
4.2%
с7
 
3.7%
я7
 
3.7%
в6
 
3.2%
Other values (32)78
41.1%
ValueCountFrequency (%)
14
 
12.2%
8
 
7.0%
8
 
7.0%
7
 
6.1%
6
 
5.2%
5
 
4.3%
5
 
4.3%
4
 
3.5%
4
 
3.5%
4
 
3.5%
Other values (27)50
43.5%
ValueCountFrequency (%)
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8)8
42.1%
ValueCountFrequency (%)
11
20.8%
8
15.1%
8
15.1%
7
13.2%
3
 
5.7%
3
 
5.7%
2
 
3.8%
2
 
3.8%
1
 
1.9%
1
 
1.9%
Other values (7)7
13.2%
ValueCountFrequency (%)
ש4
21.1%
ב3
15.8%
ר3
15.8%
ת3
15.8%
ו2
10.5%
מ2
10.5%
ע1
 
5.3%
י1
 
5.3%
ValueCountFrequency (%)
135
83.9%
22
 
13.7%
͠2
 
1.2%
1
 
0.6%
͜1
 
0.6%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
٪1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1379403
99.7%
CJK1498
 
0.1%
Misc Symbols458
 
< 0.1%
None426
 
< 0.1%
Punctuation372
 
< 0.1%
Dingbats200
 
< 0.1%
Cyrillic190
 
< 0.1%
VS157
 
< 0.1%
Katakana123
 
< 0.1%
Hiragana53
 
< 0.1%
Other values (13)112
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
192881
 
14.0%
e97893
 
7.1%
o93920
 
6.8%
t81194
 
5.9%
a79950
 
5.8%
r74729
 
5.4%
i73879
 
5.4%
n73286
 
5.3%
l40557
 
2.9%
m37603
 
2.7%
Other values (86)533511
38.7%
ValueCountFrequency (%)
ó36
 
8.5%
34
 
8.0%
32
 
7.5%
à25
 
5.9%
24
 
5.6%
23
 
5.4%
🌟18
 
4.2%
·16
 
3.8%
12
 
2.8%
11
 
2.6%
Other values (94)195
45.8%
ValueCountFrequency (%)
201
54.0%
40
 
10.8%
35
 
9.4%
34
 
9.1%
25
 
6.7%
25
 
6.7%
8
 
2.2%
2
 
0.5%
1
 
0.3%
1
 
0.3%
ValueCountFrequency (%)
238
52.0%
93
 
20.3%
32
 
7.0%
29
 
6.3%
18
 
3.9%
13
 
2.8%
9
 
2.0%
6
 
1.3%
4
 
0.9%
2
 
0.4%
Other values (12)14
 
3.1%
ValueCountFrequency (%)
29
78.4%
8
 
21.6%
ValueCountFrequency (%)
103
51.5%
14
 
7.0%
11
 
5.5%
10
 
5.0%
6
 
3.0%
6
 
3.0%
6
 
3.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
Other values (10)28
 
14.0%
ValueCountFrequency (%)
135
86.0%
22
 
14.0%
ValueCountFrequency (%)
65
 
4.3%
36
 
2.4%
32
 
2.1%
32
 
2.1%
31
 
2.1%
30
 
2.0%
29
 
1.9%
26
 
1.7%
23
 
1.5%
22
 
1.5%
Other values (331)1172
78.2%
ValueCountFrequency (%)
11
20.8%
8
15.1%
8
15.1%
7
13.2%
3
 
5.7%
3
 
5.7%
2
 
3.8%
2
 
3.8%
1
 
1.9%
1
 
1.9%
Other values (7)7
13.2%
ValueCountFrequency (%)
14
 
11.4%
8
 
6.5%
8
 
6.5%
7
 
5.7%
7
 
5.7%
6
 
4.9%
5
 
4.1%
5
 
4.1%
4
 
3.3%
4
 
3.3%
Other values (29)55
44.7%
ValueCountFrequency (%)
а24
 
12.6%
т14
 
7.4%
н14
 
7.4%
о11
 
5.8%
р11
 
5.8%
е10
 
5.3%
к8
 
4.2%
с7
 
3.7%
я7
 
3.7%
в6
 
3.2%
Other values (32)78
41.1%
ValueCountFrequency (%)
ש4
21.1%
ב3
15.8%
ר3
15.8%
ת3
15.8%
ו2
10.5%
מ2
10.5%
ע1
 
5.3%
י1
 
5.3%
ValueCountFrequency (%)
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8)8
42.1%
ValueCountFrequency (%)
🇯1
50.0%
🇵1
50.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
😍2
25.0%
🙊1
12.5%
😱1
12.5%
😃1
12.5%
😊1
12.5%
🙌1
12.5%
😌1
12.5%
ValueCountFrequency (%)
13
100.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
ValueCountFrequency (%)
٪1
100.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
͠2
66.7%
͜1
33.3%
ValueCountFrequency (%)
ʖ1
100.0%

description
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct33912
Distinct (%)94.8%
Missing1223
Missing (%)3.3%
Memory size289.3 KiB
Stay for 31+ nights (minimum nights and rates are FIRM) where you’ll have the entire apartment all to yourself at View 34. The apartment has beautiful finishes and comes fully outfitted with kitchen, bedroom, & bathroom essentials. Please note, the furnishings & room details WILL VARY as the unit is set up for you upon booking. We are an experienced professional hospitality company that works directly with the property to transform vacant units into your home away from home.<br /><br /><b>The space</b><br />We take the health and safety of guests seriously. Between each stay, the apartment is thoroughly cleaned and sanitized following guidance from the CDC. Cleaners wear protective garments (e.g., mask, gloves) and wipe surfaces, cabinet handles, door knobs, etc. with cleaning solutions that follow CDC guidance. All linens, dishware, glassware and silverware are also washed between stays. Cleaning products and tools are provided so you can clean and sanitize as well.<br /><br />We requ
 
53
Whether you are just getting away for the weekend or looking for an extended stay, we’re committed to creating comfortable experiences for our guests. We offer contact-free check-in and 24/7 virtual support which limits in-person interaction. In addition to following the guidance of the CDC and the World Health Organization, we’re partnering with sanitization experts at the Cleveland Clinic to ensure that all of our cleaning standards follow the advice of leaders in the field. We’ve put safety seals on high-touch items, stocked all spaces with complimentary hand sanitizer, and added social distancing signage in common areas. Each space is carefully designed and run by us, so you’ll always know what to expect.<br /><br />- Digital check-in<br />- Professionally cleaned<br />- 24/7 virtual concierge via text, email, or phone<br />- Private all-in-one living spaces (ample work space)<br />- Utilities included (even for longer stays)<br />- Coffee, fresh towels, and bathroom essentials pro
 
38
The apartment gives a luxurious feel with its marble bathroom, dark wooden kitchen and hardwood flooring. It is of great standard, and has a washer/dryer in unit. Fully furnished, with an equipped kitchen and everything you need to live comfortably. There are five bedrooms and two bathrooms in the apartment.<br /><br />This is a beautiful building and both the exterior and interior of it gives you a great vibe.<br /><br /><b>The space</b><br />The apartment gives a luxurious feel with its marble bathroom, dark wooden kitchen and hardwood flooring. It is of great standard, and has a washer/dryer in unit. Fully furnished, with an equipped kitchen and everything you need to live comfortably. There are five bedrooms and two bathrooms in the apartment.<br /><br />This is a beautiful building and both the exterior and interior of it gives you a great vibe.<br /><br /><b>Guest access</b><br />Apart from the private room, the guest is entitle to use the common areas of the apartment such as li
 
37
This house is located in Bed-Stuy, a charming and central Brooklyn neighborhood with plenty of restaurants, cozy bars and hip boutiques. You can explore surrounding neighborhoods like Clinton Hill, Williamsburg, and Bushwick, or hop on the subway and be in Manhattan in 30 minutes. This brand new building is home to spacious apartments with modern amenities — including a fitness center!<br /><br /><b>The space</b><br />The house is a brand new building with updated appliances, hardwood floors, large windows and in-unit washer/dryers. The Lafayette House has a spacious shared lounge for the building's 15 units, as well as a fitness center. All of the common areas are massive in comparison to your average New York City apartment. The decor is light and airy, and there's plenty of room to work from home or just hang out. This space is move-in ready; all you have to bring is your suitcase!<br /><br /><b>Guest access</b><br />The entire apartment (besides other bedrooms) is yours to call hom
 
27
Experience the best of Brooklyn’s creative scene just steps from this renovated, furnished apartment, fully equipped with everything you need to get settled in — all you have to bring is your suitcase! Walk outside and find yourself in the heart of Bushwick, renowned for its street art and bustling community. This apartment includes access to the backyard, perfect for getting time outdoors, and is just a short walk from the neighborhood’s largest park.<br /><br /><b>The space</b><br />The house has been recently renovated throughout, with split-unit heating and air conditioning, updated appliances and hardwood floors. This house is a three-level, five-unit home, with each unit equipped with a full kitchen and living room, and the first-floor unit with an additional basement common area and co-working area. The spaces are arranged around bright and inviting common areas, which are spacious in comparison to your average New York City apartment.<br /><br />The space is move-in ready; all
 
24
Other values (33907)
35610 

Length

Max length1000
Median length825
Mean length718.7498393
Min length1

Characters and Unicode

Total characters25723338
Distinct characters2225
Distinct categories23 ?
Distinct scripts13 ?
Distinct blocks27 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33139 ?
Unique (%)92.6%

Sample

1st rowBeautiful, spacious skylit studio in the heart of Midtown, Manhattan. <br /><br />STUNNING SKYLIT STUDIO / 1 BED + SINGLE / FULL BATH / FULL KITCHEN / FIREPLACE / CENTRALLY LOCATED / WiFi + APPLE TV / SHEETS + TOWELS<br /><br /><b>The space</b><br />- Spacious (500+ft²), immaculate and nicely furnished & designed studio.<br />- Tuck yourself into the ultra comfortable bed under the skylight. Fall in love with a myriad of bright lights in the city night sky. <br />- Single-sized bed/convertible floor mattress with luxury bedding (available upon request).<br />- Gorgeous pyramid skylight with amazing diffused natural light, stunning architectural details, soaring high vaulted ceilings, exposed brick, wood burning fireplace, floor seating area with natural zafu cushions, modern style mixed with eclectic art & antique treasures, large full bath, newly renovated kitchen, air conditioning/heat, high speed WiFi Internet, and Apple TV.<br />- Centrally located in the heart of Midtown Manhattan
2nd rowEnjoy 500 s.f. top floor in 1899 brownstone, w/ wood & ceramic flooring throughout, roomy bdrm, & upgraded kitchen & bathroom.  This space is unique but one of the few legal AirBnbs with a totally private bedroom, private full bathroom and private eat-in kitchen, SO PLEASE READ "THE SPACE" CAREFULLY.  It's sunny & loaded with everything you need! Your floor, and the common staircase/hallway/entryway are cleaned/sanitized per Airbnb's Enhanced Cleaning Protocol.<br /><br /><b>The space</b><br />We host on the entire top floor of our double-duplex brownstone in Clinton Hill on Gates near Classon Avenue - (7 blocks to C train, 5 blocks to G train, minutes to downtown Brooklyn & lower Manhattan).  It is not an apartment in the traditional sense, it is more of an efficiency set-up and is TOTALLY LEGAL with all short-term rental laws. The top floor for our guests consists of a sizable bedroom, full bath and eat-in kitchen for your exclusive use - you get the amenities of a private apartment
3rd row<b>The space</b><br />HELLO EVERYONE AND THANKS FOR VISITING BLISS ART SPACE! <br /><br />Thank you all for your support. I've traveled a lot in the last year few years, to the U.K. Germany, Italy and France! Loved Paris, Berlin and Calabria! Highly recommend all these places. <br /><br /><br />One room available for rent in a 2 bedroom apt in Bklyn. We share a common space with kitchen. I am an artist(painter, filmmaker) and curator who is working in the film industry while I'm building my art event production businesses.<br /><br />Price above is nightly for one person. Monthly rates available. Price is $900 per month for one person. Utilities not included, they are about 50 bucks, payable when the bill arrives mid month.<br /> <br />Couples rates are slightly more for monthly and 90$ per night short term. If you are a couple please Iet me know and I’ll give you the monthly rate for that. Room rental is on a temporary basis, perfect from 2- 6 months - no long term requests please!
4th rowPlease don’t expect the luxury here just a basic room in the center of Manhattan.<br /><br /><b>The space</b><br />You will use one large, furnished, private room of a two-bedroom apartment and share a bathroom with the host. <br /><br />The apartment is located a few blocks away from Central Park between 8th and 9th Avenue.<br />The closest subway station is Columbus Circle 59th Street. Great restaurants, Broadway and all transportation are easily accessible. <br /><br />The cost of the room is $79 per night. Weekly rate is available.<br />There is a $12.00 fee per second guest. <br /><br />The apartment also features hardwood floors and a second-floor walk-up. <br />There is a full-sized bed,TV, microwave, and a small refrigerator as well as other appliances. <br />Wired internet, WIFI, TV, electric heat, bed sheets and towels are included. <br /><br />A kitchen is not available in the living room. Please ask the host if you need.<br /><br />Basic check in/out time is 10 am. I am
5th rowOur best guests are seeking a safe, clean, spare room in a family apartment. They are comfortable being independent, accommodating of family noise (quiet hours 11pm-7am), and aren't afraid of a friendly two year old golden lab (dog). Our guests aren't put off by an old bathroom that while perfectly clean, has some peeling paint. In short, our guests want to feel like they are staying at their sister's apartment while visiting the city! (only their sister changed the sheets and cleaned).<br /><br /><b>The space</b><br />Stay in my family's little guest room and enjoy privacy, a warm welcome, and security. <br /><br />Your guest room is comfortable and clean. It is small but well outfitted, has a single bed and a fabulous mattress which is firm and yet pillowy on top, all at the same time. The bathroom is shared and immediately across the hall. ("Shared" in the sense it isn't "en suite." The family will use our second bath while you are staying with us). The bathroom is fully suppl
ValueCountFrequency (%)
Stay for 31+ nights (minimum nights and rates are FIRM) where you’ll have the entire apartment all to yourself at View 34. The apartment has beautiful finishes and comes fully outfitted with kitchen, bedroom, & bathroom essentials. Please note, the furnishings & room details WILL VARY as the unit is set up for you upon booking. We are an experienced professional hospitality company that works directly with the property to transform vacant units into your home away from home.<br /><br /><b>The space</b><br />We take the health and safety of guests seriously. Between each stay, the apartment is thoroughly cleaned and sanitized following guidance from the CDC. Cleaners wear protective garments (e.g., mask, gloves) and wipe surfaces, cabinet handles, door knobs, etc. with cleaning solutions that follow CDC guidance. All linens, dishware, glassware and silverware are also washed between stays. Cleaning products and tools are provided so you can clean and sanitize as well.<br /><br />We requ53
 
0.1%
Whether you are just getting away for the weekend or looking for an extended stay, we’re committed to creating comfortable experiences for our guests. We offer contact-free check-in and 24/7 virtual support which limits in-person interaction. In addition to following the guidance of the CDC and the World Health Organization, we’re partnering with sanitization experts at the Cleveland Clinic to ensure that all of our cleaning standards follow the advice of leaders in the field. We’ve put safety seals on high-touch items, stocked all spaces with complimentary hand sanitizer, and added social distancing signage in common areas. Each space is carefully designed and run by us, so you’ll always know what to expect.<br /><br />- Digital check-in<br />- Professionally cleaned<br />- 24/7 virtual concierge via text, email, or phone<br />- Private all-in-one living spaces (ample work space)<br />- Utilities included (even for longer stays)<br />- Coffee, fresh towels, and bathroom essentials pro38
 
0.1%
The apartment gives a luxurious feel with its marble bathroom, dark wooden kitchen and hardwood flooring. It is of great standard, and has a washer/dryer in unit. Fully furnished, with an equipped kitchen and everything you need to live comfortably. There are five bedrooms and two bathrooms in the apartment.<br /><br />This is a beautiful building and both the exterior and interior of it gives you a great vibe.<br /><br /><b>The space</b><br />The apartment gives a luxurious feel with its marble bathroom, dark wooden kitchen and hardwood flooring. It is of great standard, and has a washer/dryer in unit. Fully furnished, with an equipped kitchen and everything you need to live comfortably. There are five bedrooms and two bathrooms in the apartment.<br /><br />This is a beautiful building and both the exterior and interior of it gives you a great vibe.<br /><br /><b>Guest access</b><br />Apart from the private room, the guest is entitle to use the common areas of the apartment such as li37
 
0.1%
This house is located in Bed-Stuy, a charming and central Brooklyn neighborhood with plenty of restaurants, cozy bars and hip boutiques. You can explore surrounding neighborhoods like Clinton Hill, Williamsburg, and Bushwick, or hop on the subway and be in Manhattan in 30 minutes. This brand new building is home to spacious apartments with modern amenities — including a fitness center!<br /><br /><b>The space</b><br />The house is a brand new building with updated appliances, hardwood floors, large windows and in-unit washer/dryers. The Lafayette House has a spacious shared lounge for the building's 15 units, as well as a fitness center. All of the common areas are massive in comparison to your average New York City apartment. The decor is light and airy, and there's plenty of room to work from home or just hang out. This space is move-in ready; all you have to bring is your suitcase!<br /><br /><b>Guest access</b><br />The entire apartment (besides other bedrooms) is yours to call hom27
 
0.1%
Experience the best of Brooklyn’s creative scene just steps from this renovated, furnished apartment, fully equipped with everything you need to get settled in — all you have to bring is your suitcase! Walk outside and find yourself in the heart of Bushwick, renowned for its street art and bustling community. This apartment includes access to the backyard, perfect for getting time outdoors, and is just a short walk from the neighborhood’s largest park.<br /><br /><b>The space</b><br />The house has been recently renovated throughout, with split-unit heating and air conditioning, updated appliances and hardwood floors. This house is a three-level, five-unit home, with each unit equipped with a full kitchen and living room, and the first-floor unit with an additional basement common area and co-working area. The spaces are arranged around bright and inviting common areas, which are spacious in comparison to your average New York City apartment.<br /><br />The space is move-in ready; all 24
 
0.1%
Welcome to these brand new luxury apartments located in the artsy neighborhood of Hell’s Kitchen and close to the Theatre District. These stylish units feature spacious living areas infused with natural light, designer finishes, state-of-the-art fully-equipped kitchens, hardwood floors and a wide-range of innovative in-house amenities, including 15,500 square feet of fitness space and two breath taking zero-edge swimming pools.<br /><br /><b>The space</b><br />Experience luxury like you never have before in these 1 and 2 bedroom apartments and studios in the trendy Hell’s Kitchen. This artsy high-rise has everything you need for a stylish and modern life in Manhattan including spacious living areas, designer finishes and a wonderful array of amenities and services at your disposal. These stunning residences are thoughtfully designed to become your personal haven in the city that never sleeps. Enjoy the killer views from your living room infused with natural light, feel like a chef in t22
 
0.1%
A Statement in the Sky<br />This is not just a new building, it’s a new standard.<br />Living at The Arches means a full range of amenities that make life easier, more fun, and more productive.<br />In addition to the standard amenities, residents can enroll in The Club at The Arches* for privileged access to the more premium amenities, including fitness club, rooftop lounge, and more.<br /><br /><b>The space</b><br />Mott Haven living - The best of both worlds<br />Imagine living in a vibrant neighborhood filled with dining, nightlife, and cultural attractions.<br />Yes, that’s right, a all-in-one; This can be your new address for home, work, and play. Because, with home life and work life coming together, you want to live in a place that does it all.<br />By day, enjoy coffee shops, bookstores, cafes, retail, and more. In the evening, Bruckner Blvd. comes alive with restaurants and bars. No other borough brings together such a unique combination of cultural attractions, parks, sports18
 
< 0.1%
Experience the best of Manhattan from this spectacular building. From sweeping views to hand-picked furnishings, it’s hard to choose just a few favorite elements of this luxurious property, which features:<br />●Elegant apartments with designer kitchens and hardwood floors<br />●Stunning artwork and sophisticated design throughout the property<br />●Massive Life Time Athletic Club, basketball court, and yoga classes on-site<br />●Walkable location near the Theater District, the Javits Center, and public transit<br /><br /><b>The space</b><br />Is it a luxurious five-star hotel or an apartment building? That is the question. Combining the premium amenities of a high-end resort with the space and privacy of a home, this beautiful tower offers the epitome of sophisticated city living.<br /><br />Whether you choose to wake up like a New Yorker (bright and early!) or luxuriate for a few extra hours, the day will greet you though massive floor-to-ceiling windows. Each bed is outfitted with p18
 
< 0.1%
It’s no secret. Manhattan has the best, if not the most options for dining, shopping, and entertainment on the planet. Booking a room in the hip and cozy Staypineapple in Midtown puts you right in the heart of the action so you can get the most out of your NYC vacay. <br /><br />An amenity fee with tax ($28.69 per day) will be charged upon arrival.<br /><br />Daily pet fees apply.<br /><br /><b>The space</b><br />The rooms feature plush ambience with modern furniture to provide a peaceful night’s rest in the city that never sleeps. Enjoy the signature Naked Experience that includes duvet beds with luxury towels and robes to provide maximum comfort. Free high-speed Wi-Fi, high-def televisions with premium channels, and complimentary Kuerig coffee and tea are all standard.<br /><br />Midtown Manhattan is the home for some of New York’s top attractions. The Theater District, Central Park, Times Square, and Madison Square Garden are the most notable. With subway stops spread all over the c18
 
< 0.1%
The apartment is located in Woodside, Queens.<br />It is accessible enough to Metro and takes 7 minutes on foot to the 69st. station of MTA’s line 7, and 10 minutes to Roosevelt Ave – Jackson Heights station for 7, E, F, M and R train.<br />There are Asian supermarkets, grocery stores, banks, Seven Eleven convenience store, restaurants and bars near subway station. It takes 30 minutes approximately for Manhattan.<br />store are a few minutes from the apartment.<br /><br /><b>The space</b><br />The building has three stories: the apartment for rent is 3rd floor<br /><br /><b>Other things to note</b><br />***** Before booking***********************<br />This is NOT like HOTEL, HOSTEL, GUEST HOUSE...<br />This house is a nomal shared house in New York.<br />You have housemates.<br />I ask guests to prepare your amenity by yourself.<br />There is no hoetl service like daily clean, 24 hour security guard etc.<br />*There are basic kitchen equipments like dishes, silver, microwaves, frying 16
 
< 0.1%
Other values (33902)35518
96.0%
(Missing)1223
 
3.3%
2021-04-12T21:32:40.921639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the174623
 
4.2%
and164229
 
3.9%
a122285
 
2.9%
br110595
 
2.6%
to98955
 
2.4%
in81557
 
1.9%
is79179
 
1.9%
with65704
 
1.6%
of63251
 
1.5%
apartment45301
 
1.1%
Other values (62429)3194188
76.1%

Most occurring characters

ValueCountFrequency (%)
4207359
16.4%
e2089115
 
8.1%
a1590193
 
6.2%
t1523319
 
5.9%
o1480061
 
5.8%
r1451917
 
5.6%
n1257962
 
4.9%
i1239879
 
4.8%
s1146817
 
4.5%
l820878
 
3.2%
Other values (2215)8915838
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter18507278
71.9%
Space Separator4208286
 
16.4%
Uppercase Letter987961
 
3.8%
Other Punctuation961838
 
3.7%
Math Symbol710352
 
2.8%
Decimal Number184838
 
0.7%
Dash Punctuation68085
 
0.3%
Other Letter28161
 
0.1%
Close Punctuation24711
 
0.1%
Open Punctuation23431
 
0.1%
Other values (13)18397
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
513
 
1.8%
453
 
1.6%
352
 
1.2%
339
 
1.2%
289
 
1.0%
237
 
0.8%
236
 
0.8%
229
 
0.8%
215
 
0.8%
214
 
0.8%
Other values (1645)25084
89.1%
ValueCountFrequency (%)
395
20.8%
258
13.6%
148
 
7.8%
145
 
7.6%
141
 
7.4%
44
 
2.3%
38
 
2.0%
36
 
1.9%
31
 
1.6%
20
 
1.1%
Other values (209)643
33.9%
ValueCountFrequency (%)
e2089115
11.3%
a1590193
 
8.6%
t1523319
 
8.2%
o1480061
 
8.0%
r1451917
 
7.8%
n1257962
 
6.8%
i1239879
 
6.7%
s1146817
 
6.2%
l820878
 
4.4%
h760985
 
4.1%
Other values (102)5146152
27.8%
ValueCountFrequency (%)
T136087
 
13.8%
S64027
 
6.5%
C60789
 
6.2%
A60001
 
6.1%
B56080
 
5.7%
I51679
 
5.2%
N48187
 
4.9%
M47300
 
4.8%
E46890
 
4.7%
W40027
 
4.1%
Other values (77)376894
38.1%
ValueCountFrequency (%)
/332827
34.6%
,263350
27.4%
.251444
26.1%
!29795
 
3.1%
'23136
 
2.4%
*19297
 
2.0%
:12210
 
1.3%
&12035
 
1.3%
"4234
 
0.4%
;3453
 
0.4%
Other values (30)10057
 
1.0%
ValueCountFrequency (%)
138834
21.0%
237654
20.4%
027580
14.9%
522478
12.2%
318947
10.3%
415656
8.5%
77117
 
3.9%
66602
 
3.6%
85385
 
2.9%
94537
 
2.5%
Other values (8)48
 
< 0.1%
ValueCountFrequency (%)
<353501
49.8%
>352654
49.6%
+2660
 
0.4%
=690
 
0.1%
~596
 
0.1%
142
 
< 0.1%
|84
 
< 0.1%
×9
 
< 0.1%
6
 
< 0.1%
5
 
< 0.1%
Other values (2)5
 
< 0.1%
ValueCountFrequency (%)
166
84.7%
13
 
6.6%
ً4
 
2.0%
3
 
1.5%
2
 
1.0%
2
 
1.0%
2
 
1.0%
2
 
1.0%
1
 
0.5%
̈1
 
0.5%
ValueCountFrequency (%)
^40
30.8%
`32
24.6%
´29
22.3%
🏻12
 
9.2%
🏼7
 
5.4%
🏽6
 
4.6%
¨2
 
1.5%
🏾1
 
0.8%
¸1
 
0.8%
ValueCountFrequency (%)
935
84.7%
123
 
11.1%
25
 
2.3%
6
 
0.5%
6
 
0.5%
4
 
0.4%
­3
 
0.3%
1
 
0.1%
1
 
0.1%
ValueCountFrequency (%)
(23171
98.9%
[105
 
0.4%
82
 
0.3%
49
 
0.2%
{14
 
0.1%
8
 
< 0.1%
2
 
< 0.1%
ValueCountFrequency (%)
)24447
98.9%
]105
 
0.4%
87
 
0.4%
49
 
0.2%
}13
 
0.1%
8
 
< 0.1%
2
 
< 0.1%
ValueCountFrequency (%)
²33
60.0%
½18
32.7%
¾1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
ValueCountFrequency (%)
$2938
99.6%
3
 
0.1%
¤3
 
0.1%
¥2
 
0.1%
2
 
0.1%
¢1
 
< 0.1%
ValueCountFrequency (%)
4207359
> 99.9%
 824
 
< 0.1%
 58
 
< 0.1%
42
 
< 0.1%
3
 
< 0.1%
ValueCountFrequency (%)
-66605
97.8%
837
 
1.2%
632
 
0.9%
9
 
< 0.1%
2
 
< 0.1%
ValueCountFrequency (%)
314
99.1%
1
 
0.3%
1
 
0.3%
1
 
0.3%
ValueCountFrequency (%)
9508
92.4%
781
 
7.6%
»4
 
< 0.1%
ValueCountFrequency (%)
727
91.2%
69
 
8.7%
«1
 
0.1%
ValueCountFrequency (%)
9
60.0%
5
33.3%
1
 
6.7%
ValueCountFrequency (%)
213
97.7%
4
 
1.8%
1
 
0.5%
ValueCountFrequency (%)
_422
100.0%
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin19490957
75.8%
Common6198940
 
24.1%
Han22622
 
0.1%
Cyrillic4250
 
< 0.1%
Hiragana2302
 
< 0.1%
Katakana2171
 
< 0.1%
Inherited1144
 
< 0.1%
Hangul860
 
< 0.1%
Thai24
 
< 0.1%
Arabic18
 
< 0.1%
Other values (3)50
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
513
 
2.3%
453
 
2.0%
352
 
1.6%
339
 
1.5%
289
 
1.3%
237
 
1.0%
236
 
1.0%
229
 
1.0%
215
 
1.0%
209
 
0.9%
Other values (1242)19550
86.4%
ValueCountFrequency (%)
4207359
67.9%
<353501
 
5.7%
>352654
 
5.7%
/332827
 
5.4%
,263350
 
4.2%
.251444
 
4.1%
-66605
 
1.1%
138834
 
0.6%
237654
 
0.6%
!29795
 
0.5%
Other values (380)264917
 
4.3%
ValueCountFrequency (%)
32
 
3.7%
30
 
3.5%
28
 
3.3%
21
 
2.4%
20
 
2.3%
18
 
2.1%
17
 
2.0%
17
 
2.0%
17
 
2.0%
16
 
1.9%
Other values (229)644
74.9%
ValueCountFrequency (%)
e2089115
 
10.7%
a1590193
 
8.2%
t1523319
 
7.8%
o1480061
 
7.6%
r1451917
 
7.4%
n1257962
 
6.5%
i1239879
 
6.4%
s1146817
 
5.9%
l820878
 
4.2%
h760985
 
3.9%
Other values (99)6129831
31.4%
ValueCountFrequency (%)
166
 
7.6%
143
 
6.6%
139
 
6.4%
125
 
5.8%
111
 
5.1%
109
 
5.0%
108
 
5.0%
87
 
4.0%
68
 
3.1%
62
 
2.9%
Other values (63)1053
48.5%
ValueCountFrequency (%)
214
 
9.3%
204
 
8.9%
146
 
6.3%
134
 
5.8%
129
 
5.6%
123
 
5.3%
108
 
4.7%
95
 
4.1%
85
 
3.7%
80
 
3.5%
Other values (50)984
42.7%
ValueCountFrequency (%)
о464
 
10.9%
а363
 
8.5%
е313
 
7.4%
н295
 
6.9%
т282
 
6.6%
и265
 
6.2%
р220
 
5.2%
с200
 
4.7%
м174
 
4.1%
к158
 
3.7%
Other values (44)1516
35.7%
ValueCountFrequency (%)
נ2
11.8%
ב2
11.8%
ר2
11.8%
י2
11.8%
׳1
 
5.9%
א1
 
5.9%
ח1
 
5.9%
ו1
 
5.9%
מ1
 
5.9%
ד1
 
5.9%
Other values (3)3
17.6%
ValueCountFrequency (%)
4
16.7%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
ValueCountFrequency (%)
3
16.7%
3
16.7%
3
16.7%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
ValueCountFrequency (%)
935
81.7%
166
 
14.5%
25
 
2.2%
13
 
1.1%
ً4
 
0.3%
̈1
 
0.1%
ValueCountFrequency (%)
ه4
22.2%
ل4
22.2%
ا4
22.2%
أ2
11.1%
و2
11.1%
س2
11.1%
ValueCountFrequency (%)
9
60.0%
5
33.3%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII25664740
99.8%
CJK22618
 
0.1%
Punctuation17068
 
0.1%
None5885
 
< 0.1%
Cyrillic4250
 
< 0.1%
Katakana3396
 
< 0.1%
Hiragana2302
 
< 0.1%
Hangul860
 
< 0.1%
Misc Symbols694
 
< 0.1%
Geometric Shapes506
 
< 0.1%
Other values (17)1019
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
4207359
16.4%
e2089115
 
8.1%
a1590193
 
6.2%
t1523319
 
5.9%
o1480061
 
5.8%
r1451917
 
5.7%
n1257962
 
4.9%
i1239879
 
4.8%
s1146817
 
4.5%
l820878
 
3.2%
Other values (88)8857240
34.5%
ValueCountFrequency (%)
910
15.5%
 824
14.0%
721
12.3%
é521
 
8.9%
375
 
6.4%
ó258
 
4.4%
ñ200
 
3.4%
194
 
3.3%
á194
 
3.3%
º148
 
2.5%
Other values (244)1540
26.2%
ValueCountFrequency (%)
9508
55.7%
3202
 
18.8%
935
 
5.5%
837
 
4.9%
781
 
4.6%
727
 
4.3%
632
 
3.7%
123
 
0.7%
69
 
0.4%
67
 
0.4%
Other values (15)187
 
1.1%
ValueCountFrequency (%)
9
60.0%
5
33.3%
1
 
6.7%
ValueCountFrequency (%)
145
52.3%
38
 
13.7%
18
 
6.5%
13
 
4.7%
13
 
4.7%
9
 
3.2%
7
 
2.5%
4
 
1.4%
4
 
1.4%
4
 
1.4%
Other values (12)22
 
7.9%
ValueCountFrequency (%)
166
92.7%
13
 
7.3%
ValueCountFrequency (%)
395
56.9%
141
 
20.3%
31
 
4.5%
20
 
2.9%
14
 
2.0%
14
 
2.0%
12
 
1.7%
11
 
1.6%
9
 
1.3%
8
 
1.2%
Other values (14)39
 
5.6%
ValueCountFrequency (%)
258
51.0%
148
29.2%
36
 
7.1%
19
 
3.8%
16
 
3.2%
9
 
1.8%
8
 
1.6%
4
 
0.8%
4
 
0.8%
2
 
0.4%
Other values (2)2
 
0.4%
ValueCountFrequency (%)
44
100.0%
ValueCountFrequency (%)
ه4
18.2%
ل4
18.2%
ا4
18.2%
ً4
18.2%
أ2
9.1%
و2
9.1%
س2
9.1%
ValueCountFrequency (%)
513
 
2.3%
453
 
2.0%
352
 
1.6%
339
 
1.5%
289
 
1.3%
237
 
1.0%
236
 
1.0%
229
 
1.0%
215
 
1.0%
209
 
0.9%
Other values (1241)19546
86.4%
ValueCountFrequency (%)
3
16.7%
3
16.7%
3
16.7%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
ValueCountFrequency (%)
214
 
9.3%
204
 
8.9%
146
 
6.3%
134
 
5.8%
129
 
5.6%
123
 
5.3%
108
 
4.7%
95
 
4.1%
85
 
3.7%
80
 
3.5%
Other values (50)984
42.7%
ValueCountFrequency (%)
32
 
3.7%
30
 
3.5%
28
 
3.3%
21
 
2.4%
20
 
2.3%
18
 
2.1%
17
 
2.0%
17
 
2.0%
17
 
2.0%
16
 
1.9%
Other values (229)644
74.9%
ValueCountFrequency (%)
4
16.7%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
2
8.3%
ValueCountFrequency (%)
о464
 
10.9%
а363
 
8.5%
е313
 
7.4%
н295
 
6.9%
т282
 
6.6%
и265
 
6.2%
р220
 
5.2%
с200
 
4.7%
м174
 
4.1%
к158
 
3.7%
Other values (44)1516
35.7%
ValueCountFrequency (%)
142
98.6%
2
 
1.4%
ValueCountFrequency (%)
1017
29.9%
213
 
6.3%
166
 
4.9%
143
 
4.2%
139
 
4.1%
125
 
3.7%
111
 
3.3%
109
 
3.2%
108
 
3.2%
87
 
2.6%
Other values (60)1178
34.7%
ValueCountFrequency (%)
נ2
11.8%
ב2
11.8%
ר2
11.8%
י2
11.8%
׳1
 
5.9%
א1
 
5.9%
ח1
 
5.9%
ו1
 
5.9%
מ1
 
5.9%
ד1
 
5.9%
Other values (3)3
17.6%
ValueCountFrequency (%)
😊20
25.6%
🙏8
 
10.3%
😉7
 
9.0%
😀6
 
7.7%
😂6
 
7.7%
😁5
 
6.4%
😍4
 
5.1%
🙂4
 
5.1%
😎2
 
2.6%
😄2
 
2.6%
Other values (13)14
17.9%
ValueCountFrequency (%)
4
100.0%
ValueCountFrequency (%)
̈1
100.0%
ValueCountFrequency (%)
6
100.0%
ValueCountFrequency (%)
🇵1
50.0%
🇷1
50.0%
ValueCountFrequency (%)
4
100.0%
ValueCountFrequency (%)
2
100.0%
ValueCountFrequency (%)
𝗼14
 
7.7%
𝗿14
 
7.7%
𝘂13
 
7.1%
𝗲11
 
6.0%
𝘀11
 
6.0%
𝗻11
 
6.0%
𝗶10
 
5.5%
𝗵10
 
5.5%
𝘁8
 
4.4%
𝗮8
 
4.4%
Other values (28)72
39.6%

neighborhood_overview
Categorical

HIGH CARDINALITY
MISSING

Distinct19385
Distinct (%)83.1%
Missing13683
Missing (%)37.0%
Memory size289.3 KiB
This furnished apartment is located in Midtown. As the central portion of Manhattan it is a one-of-a-kind area. Home to some of the city’s most iconic sights, including Rockefeller Center, the Chrysler Building, Broadway, Times Square, the Empire State Building and the United Nations Headquarters. Considered the island’s central business district, it offers an abundance of hot spots. Niche destinations such as Koreatown can also be found in Midtown. Bordering Central Park, it is a vast neighborhood that encompasses the city center. Without traffic, JFK Airport is about half an hour away by car.
 
45
The building is in the Financial District, a humming business area located at the tip og Manhattan, New York. Enjoy late night runs along Battery Park and East River, or a late evening drink in Stone Street. On Stone Street you can find many bars and restaurants creating the good after-work vibes. Beautiful parks and charming, walkable streets make FiDi a lovely place to live. Near major transportation such as the South Ferry and several train stations, it is a great location to move around for small or bigger get-aways.
 
44
The surroundings of the apartment are a commuter town, but not noisy and comfortable to live in. A laundromat and a grocery
 
39
We're located in a safe and quiet residential neighborhood on Manhattan's East Side, yet we're within walking distance of Broadway theaters, Grand Central Station, the United Nations, the Empire State Building and the city’s many museums.
 
38
Welcome to Hell's Kitchen – one of New Yorks' most desired places to live. Situated between 30th and 59th streets and extending from Eighth Avenue to the Hudson River, Hell's Kitchen is a lively neighborhood in Midtown Manhattan. This neighborhood was originally named after a notorious motorcycle gang of the 19th century, but now exists as a peaceful and elevated pocket of NYC.<br /><br />Enjoy an eclectic array of world-class cuisine on your doorstep. Hell’s Kitchen is home to some of New York’s most popular restaurants. With The Method Japanese Kitchen and Bar on one side, and other eateries such as the Five Napkin Burger and Pam Real Thai on the other, you’’ never be hungry, or bored. Enjoy easy access to all of MTA’s subway lines, or a quick escape to Upstate New York for a nature-filled weekend getaway.<br /><br />Hell’s Kitchen is a great location to live in. June Homes has made that easier by providing 1 to 12-month rental agreements. Instead of looking for a sublet, you can com
 
37
Other values (19380)
23126 

Length

Max length1000
Median length284
Mean length360.6844271
Min length1

Characters and Unicode

Total characters8414407
Distinct characters1059
Distinct categories21 ?
Distinct scripts9 ?
Distinct blocks18 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18018 ?
Unique (%)77.2%

Sample

1st rowCentrally located in the heart of Manhattan just a few blocks from all subway connections in the very desirable Midtown location a few minutes walk to Times Square, the Theater District, Bryant Park and Herald Square.
2nd rowJust the right mix of urban center and local neighborhood; close to all but enough quiet for a calming walk. 15 to 45 minutes to most parts of Manhattan; 10 to 30 minutes to most Brooklyn points of interest; 45 minutes to 60 minutes to historic Coney Island.
3rd rowTheater district, many restaurants around here.
4th rowOur neighborhood is full of restaurants and cafes. There is plenty to do.
5th rowNeighborhood is amazing!<br />Best subways to Manhattan, Williamsburg, Lower East Side (20 mins);<br />* Excellent affordable restaurants; Supermarket on corner.<br />* Close to Barclay's Center, Bell House, other good music clubs, cultural events;<br />* Near Prospect Park (free events, concerts) & Botanical Gardens <br />* Museum / Brooklyn Academy of Music <br />* Steps from NY Marathon route<br />* Flea Markets & bargain shopping<br />* YMCA, 5 gyms nearby; Street parking.
ValueCountFrequency (%)
This furnished apartment is located in Midtown. As the central portion of Manhattan it is a one-of-a-kind area. Home to some of the city’s most iconic sights, including Rockefeller Center, the Chrysler Building, Broadway, Times Square, the Empire State Building and the United Nations Headquarters. Considered the island’s central business district, it offers an abundance of hot spots. Niche destinations such as Koreatown can also be found in Midtown. Bordering Central Park, it is a vast neighborhood that encompasses the city center. Without traffic, JFK Airport is about half an hour away by car.45
 
0.1%
The building is in the Financial District, a humming business area located at the tip og Manhattan, New York. Enjoy late night runs along Battery Park and East River, or a late evening drink in Stone Street. On Stone Street you can find many bars and restaurants creating the good after-work vibes. Beautiful parks and charming, walkable streets make FiDi a lovely place to live. Near major transportation such as the South Ferry and several train stations, it is a great location to move around for small or bigger get-aways.44
 
0.1%
The surroundings of the apartment are a commuter town, but not noisy and comfortable to live in. A laundromat and a grocery39
 
0.1%
We're located in a safe and quiet residential neighborhood on Manhattan's East Side, yet we're within walking distance of Broadway theaters, Grand Central Station, the United Nations, the Empire State Building and the city’s many museums.38
 
0.1%
Welcome to Hell's Kitchen – one of New Yorks' most desired places to live. Situated between 30th and 59th streets and extending from Eighth Avenue to the Hudson River, Hell's Kitchen is a lively neighborhood in Midtown Manhattan. This neighborhood was originally named after a notorious motorcycle gang of the 19th century, but now exists as a peaceful and elevated pocket of NYC.<br /><br />Enjoy an eclectic array of world-class cuisine on your doorstep. Hell’s Kitchen is home to some of New York’s most popular restaurants. With The Method Japanese Kitchen and Bar on one side, and other eateries such as the Five Napkin Burger and Pam Real Thai on the other, you’’ never be hungry, or bored. Enjoy easy access to all of MTA’s subway lines, or a quick escape to Upstate New York for a nature-filled weekend getaway.<br /><br />Hell’s Kitchen is a great location to live in. June Homes has made that easier by providing 1 to 12-month rental agreements. Instead of looking for a sublet, you can com37
 
0.1%
Located in the heart of midtown Manhattan, View 34 is walking distance to the East River, NYU Medical Center and numerous bars and restaurants.37
 
0.1%
This furnished apartment is located in the Financial District, also known as FiDi. Home to Wall Street, One World Trade Center, the South Street Seaport, and Bowling Green it is a constant hub of activity. During the week the sidewalk is always bustling and the restaurants are filled with professionals. The glittering skyscrapers and well-known landmarks make this one of the city’s most recognizable and historic neighborhoods. By subway, Times Square is about 20 minutes away.36
 
0.1%
Jackson Heights Queens is a residential neighborhood. <br />There are supermarkets, pharmacies, restaurants, bars , banks(Chase, Citibank, TD bank, Bank of America). <br />Around station, there are some Indian restaurants, traditional stores, supermarkets. I can spend and enjoy your time there too!<br /><br />Jackson Heights is just 15-20min from Manhattan.<br />You will be able to have a great stay in this area,Jackson Heights.35
 
0.1%
The Greenpoint House in only a few short blocks from the East River in Brooklyn, nestled among restaurants, coffee shops and a collection of cozy brick apartment buildings. The nearby waterfront is scattered with green spaces and high rises, or you can opt to explore the neighborhood’s historic Polish shops and eateries.33
 
0.1%
This coliving space is located in the Bushwick neighborhood in North Brooklyn, in an area known for its creative scene and nightlife. The house has plenty of cafes, restaurants and bars within walking distance, and is located near some of Bushwick’s most beloved murals. You can also walk to Maria Hernandez Park, a large park that serves as a community gathering center for many Bushwick residents.33
 
0.1%
Other values (19375)22952
62.0%
(Missing)13683
37.0%
2021-04-12T21:32:41.322292image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the68496
 
5.0%
and60409
 
4.4%
of34691
 
2.5%
a34277
 
2.5%
is31773
 
2.3%
to31738
 
2.3%
in21527
 
1.6%
br15365
 
1.1%
neighborhood13916
 
1.0%
restaurants12862
 
0.9%
Other values (30842)1056075
76.5%

Most occurring characters

ValueCountFrequency (%)
1369069
16.3%
e694946
 
8.3%
a578467
 
6.9%
t528843
 
6.3%
o502836
 
6.0%
r478782
 
5.7%
n462038
 
5.5%
s433629
 
5.2%
i429044
 
5.1%
l268220
 
3.2%
Other values (1049)2668533
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6248582
74.3%
Space Separator1369798
 
16.3%
Uppercase Letter359782
 
4.3%
Other Punctuation255548
 
3.0%
Math Symbol67183
 
0.8%
Decimal Number56752
 
0.7%
Dash Punctuation21651
 
0.3%
Close Punctuation9247
 
0.1%
Open Punctuation8989
 
0.1%
Other Letter7544
 
0.1%
Other values (11)9331
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
165
 
2.2%
140
 
1.9%
139
 
1.8%
129
 
1.7%
121
 
1.6%
112
 
1.5%
109
 
1.4%
º105
 
1.4%
104
 
1.4%
95
 
1.3%
Other values (719)6325
83.8%
ValueCountFrequency (%)
e694946
11.1%
a578467
 
9.3%
t528843
 
8.5%
o502836
 
8.0%
r478782
 
7.7%
n462038
 
7.4%
s433629
 
6.9%
i429044
 
6.9%
l268220
 
4.3%
h262381
 
4.2%
Other values (93)1609396
25.8%
ValueCountFrequency (%)
36
 
11.8%
25
 
8.2%
21
 
6.9%
21
 
6.9%
18
 
5.9%
15
 
4.9%
14
 
4.6%
13
 
4.2%
9
 
2.9%
°6
 
2.0%
Other values (70)128
41.8%
ValueCountFrequency (%)
T32532
 
9.0%
S29866
 
8.3%
B29350
 
8.2%
C29004
 
8.1%
M25255
 
7.0%
A20518
 
5.7%
P20227
 
5.6%
N16693
 
4.6%
I15825
 
4.4%
W15804
 
4.4%
Other values (44)124708
34.7%
ValueCountFrequency (%)
,104682
41.0%
.77141
30.2%
/39085
 
15.3%
'12788
 
5.0%
!7511
 
2.9%
:4450
 
1.7%
&2722
 
1.1%
"1980
 
0.8%
1642
 
0.6%
;1131
 
0.4%
Other values (18)2416
 
0.9%
ValueCountFrequency (%)
112261
21.6%
09739
17.2%
29033
15.9%
57949
14.0%
34742
 
8.4%
44229
 
7.5%
72511
 
4.4%
62385
 
4.2%
92220
 
3.9%
81663
 
2.9%
Other values (2)20
 
< 0.1%
ValueCountFrequency (%)
>33141
49.3%
<33138
49.3%
=327
 
0.5%
+303
 
0.5%
182
 
0.3%
~64
 
0.1%
|20
 
< 0.1%
7
 
< 0.1%
1
 
< 0.1%
ValueCountFrequency (%)
1023
89.2%
108
 
9.4%
11
 
1.0%
­2
 
0.2%
2
 
0.2%
1
 
0.1%
ValueCountFrequency (%)
1369069
99.9%
 599
 
< 0.1%
110
 
< 0.1%
 18
 
< 0.1%
2
 
< 0.1%
ValueCountFrequency (%)
(8860
98.6%
[108
 
1.2%
9
 
0.1%
9
 
0.1%
{3
 
< 0.1%
ValueCountFrequency (%)
)9113
98.6%
]108
 
1.2%
13
 
0.1%
9
 
0.1%
}4
 
< 0.1%
ValueCountFrequency (%)
`10
52.6%
´6
31.6%
🏾1
 
5.3%
🏼1
 
5.3%
🏽1
 
5.3%
ValueCountFrequency (%)
-19829
91.6%
1203
 
5.6%
615
 
2.8%
4
 
< 0.1%
ValueCountFrequency (%)
347
80.3%
83
 
19.2%
«2
 
0.5%
ValueCountFrequency (%)
5450
94.7%
302
 
5.2%
»2
 
< 0.1%
ValueCountFrequency (%)
½5
83.3%
¼1
 
16.7%
ValueCountFrequency (%)
216
96.0%
9
 
4.0%
ValueCountFrequency (%)
$262
100.0%
ValueCountFrequency (%)
15
100.0%
ValueCountFrequency (%)
_70
100.0%
ValueCountFrequency (%)
1095
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6607258
78.5%
Common1797471
 
21.4%
Han4333
 
0.1%
Hiragana1890
 
< 0.1%
Cyrillic1182
 
< 0.1%
Katakana1113
 
< 0.1%
Inherited1049
 
< 0.1%
Hangul110
 
< 0.1%
Bopomofo1
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
139
 
3.2%
76
 
1.8%
73
 
1.7%
71
 
1.6%
便66
 
1.5%
65
 
1.5%
64
 
1.5%
60
 
1.4%
59
 
1.4%
59
 
1.4%
Other values (549)3601
83.1%
ValueCountFrequency (%)
1369069
76.2%
,104682
 
5.8%
.77141
 
4.3%
/39085
 
2.2%
>33141
 
1.8%
<33138
 
1.8%
-19829
 
1.1%
'12788
 
0.7%
112261
 
0.7%
09739
 
0.5%
Other values (180)86598
 
4.8%
ValueCountFrequency (%)
e694946
 
10.5%
a578467
 
8.8%
t528843
 
8.0%
o502836
 
7.6%
r478782
 
7.2%
n462038
 
7.0%
s433629
 
6.6%
i429044
 
6.5%
l268220
 
4.1%
h262381
 
4.0%
Other values (81)1968072
29.8%
ValueCountFrequency (%)
4
 
3.6%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
2
 
1.8%
Other values (64)79
71.8%
ValueCountFrequency (%)
165
 
8.7%
140
 
7.4%
129
 
6.8%
121
 
6.4%
112
 
5.9%
104
 
5.5%
95
 
5.0%
81
 
4.3%
77
 
4.1%
73
 
3.9%
Other values (38)793
42.0%
ValueCountFrequency (%)
о144
 
12.2%
а112
 
9.5%
т86
 
7.3%
н81
 
6.9%
е74
 
6.3%
и65
 
5.5%
р54
 
4.6%
с54
 
4.6%
м45
 
3.8%
к41
 
3.5%
Other values (37)426
36.0%
ValueCountFrequency (%)
109
 
9.8%
66
 
5.9%
65
 
5.8%
55
 
4.9%
55
 
4.9%
52
 
4.7%
50
 
4.5%
49
 
4.4%
45
 
4.0%
45
 
4.0%
Other values (36)522
46.9%
ValueCountFrequency (%)
1023
97.5%
15
 
1.4%
11
 
1.0%
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8391800
99.7%
Punctuation11014
 
0.1%
CJK4324
 
0.1%
None2314
 
< 0.1%
Hiragana1890
 
< 0.1%
Katakana1331
 
< 0.1%
Cyrillic1182
 
< 0.1%
Arrows182
 
< 0.1%
Hangul110
 
< 0.1%
Geometric Shapes87
 
< 0.1%
Other values (8)173
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
1369069
16.3%
e694946
 
8.3%
a578467
 
6.9%
t528843
 
6.3%
o502836
 
6.0%
r478782
 
5.7%
n462038
 
5.5%
s433629
 
5.2%
i429044
 
5.1%
l268220
 
3.2%
Other values (85)2645926
31.5%
ValueCountFrequency (%)
5450
49.5%
1642
 
14.9%
1203
 
10.9%
1023
 
9.3%
615
 
5.6%
347
 
3.2%
302
 
2.7%
110
 
1.0%
108
 
1.0%
92
 
0.8%
Other values (8)122
 
1.1%
ValueCountFrequency (%)
 599
25.9%
é400
17.3%
166
 
7.2%
160
 
6.9%
135
 
5.8%
º105
 
4.5%
á99
 
4.3%
98
 
4.2%
·83
 
3.6%
ó63
 
2.7%
Other values (111)406
17.5%
ValueCountFrequency (%)
😍4
30.8%
🙏2
15.4%
😊2
15.4%
😉2
15.4%
🙂1
 
7.7%
😱1
 
7.7%
😁1
 
7.7%
ValueCountFrequency (%)
139
 
3.2%
76
 
1.8%
73
 
1.7%
71
 
1.6%
便66
 
1.5%
65
 
1.5%
64
 
1.5%
60
 
1.4%
59
 
1.4%
59
 
1.4%
Other values (548)3592
83.1%
ValueCountFrequency (%)
25
32.1%
15
19.2%
14
17.9%
13
16.7%
9
 
11.5%
1
 
1.3%
1
 
1.3%
ValueCountFrequency (%)
15
100.0%
ValueCountFrequency (%)
21
80.8%
4
 
15.4%
1
 
3.8%
ValueCountFrequency (%)
36
41.4%
21
24.1%
18
20.7%
4
 
4.6%
3
 
3.4%
3
 
3.4%
2
 
2.3%
ValueCountFrequency (%)
165
 
8.7%
140
 
7.4%
129
 
6.8%
121
 
6.4%
112
 
5.9%
104
 
5.5%
95
 
5.0%
81
 
4.3%
77
 
4.1%
73
 
3.9%
Other values (38)793
42.0%
ValueCountFrequency (%)
216
 
16.2%
109
 
8.2%
66
 
5.0%
65
 
4.9%
55
 
4.1%
55
 
4.1%
52
 
3.9%
50
 
3.8%
49
 
3.7%
45
 
3.4%
Other values (38)569
42.7%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
о144
 
12.2%
а112
 
9.5%
т86
 
7.3%
н81
 
6.9%
е74
 
6.3%
и65
 
5.5%
р54
 
4.6%
с54
 
4.6%
м45
 
3.8%
к41
 
3.5%
Other values (37)426
36.0%
ValueCountFrequency (%)
4
 
3.6%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
2
 
1.8%
Other values (64)79
71.8%
ValueCountFrequency (%)
182
100.0%
ValueCountFrequency (%)
3
100.0%
ValueCountFrequency (%)
7
100.0%
ValueCountFrequency (%)
𝗼4
 
13.3%
𝗶3
 
10.0%
𝗧2
 
6.7%
𝗵2
 
6.7%
𝗻2
 
6.7%
𝗰2
 
6.7%
𝗲1
 
3.3%
𝗛1
 
3.3%
𝘂1
 
3.3%
𝗯1
 
3.3%
Other values (11)11
36.7%
Distinct4000
Distinct (%)10.8%
Missing18
Missing (%)< 0.1%
Memory size289.3 KiB
Minimum2008-08-22 00:00:00
Maximum2021-02-02 00:00:00
2021-04-12T21:32:41.487814image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:41.641096image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

host_about
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MISSING

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Why take a chance picking & choosing between so many individual hosts when you can enjoy the highest-quality guest experience from one consistent host -- Blueground. We are a global real estate tech company offering +3500 fully-equipped & furnished apartments for a month, a year or longer across 12 cities and 3 continents. Centrally-based in vibrant neighborhoods, each home is tech-powered & furnished by our expert Interior Design teams. Enjoy at-home amenities like high-speed WiFi, a fully-stocked kitchen, smart TV, premium bedding/towels, quality toiletries, and depending on the apartment choice -- artisan coffee, bluetooth speakers & select building amenities such as pools, gyms & outdoor spaces. From meal, wine & grocery delivery to laundry & dry-cleaning right to your door, our guests can choose from a number of service benefits. Each apartment is safe & professionally sanitized. During your stay Driven by a mission to help you show up & start living, Blueground is proud to host thousands of guests around the world in the following cities: New York, Los Angeles, San Francisco, Boston, Chicago, Washington D.C., Seattle, Dubai, Istanbul, Paris, London and Athens. Upon arrival, you’ll either be greeted personally by a Blueground team member or given self check-in instructions. The entire apartment is yours to enjoy; and for additional support, our Client Experience team is available via phone, email & our Guest App through which you can schedule additional cleanings, request fresh towels/linens, submit maintenance requests, and view neighborhood recommendations. We’ll share all details upon confirmation of your stay.
 
255
At June Homes, our mission is to make renting an apartment as easy and stress-free as possible. We make applying simple and seamless, charge no hidden fees, and take care of the little things. All of our homes are fully furnished, and include Netflix/HBO, monthly delivery of home supplies, WiFi and utilities for $125-$200/month. If you have any issues, we’re available with 24-hour support. All of our apartments are available with flexible terms, meaning you can lease for 1–18 months. New to the city? Consider moving in for two months and then trying out a new neighborhood. Need a roommate? We also offer shared homes to our member-only community. Our design team ensures that each home meets our elevated standards, and you can select between furnished or unfurnished. It’s your call. It’s your home.
 
181
Dear Airbnb guests! I manage some co-living spaces in Manhattan, Queens, and Brooklyn with my team members. I have been managing shared apartments for a decade and had people from 74 different countries so far :) Please feel free to ask me any questions! *I can speak Japanese as well! Please feel free to contact me in Japanese if you do. Who we are: Our Principles 1) Growing Our Alumni Community: We don’t require membership fees to maximize our profits. Instead, our focus is on growing our alumni community. We believe that our services and fair pricing speak for themselves among our guests. Our alumni posted 200+ reviews in 2019. What’s more, 75% of the reviews gave us five stars and 97% awarded more than four stars. Our alumni community spans the globe with 74 unique nationalities, and it has been expanding mostly by word of mouth. We look forward to serving all our new guests: our alumni of tomorrow. ‍ ‍2) Transparency. One All-Inclusive Price. That’s What We’re About: There’s no math required. The price for our one-month minimum stay is simple and fair, no matter how long you stay with us. Our one-month price is already competitive (averaging $1,100 to $1,500, with 90% of our 150 rooms under $1,650 per month), compared to others’ discounted prices for three- to six-month stays. In 2019, 30%+ of our customers extended their original stay by a few months. There’s really no substitute for an all-inclusive co-living environment, with a furnished private room, that’s ready for you on day one. ‍ ‍3) Increasing Value for the Local Property Industry: We provide co-living communities for our guests by helping property owners draw more value from under-managed residential properties. We care about our customer community, of course, but we’re also excited about uniting property owners, vendors, and our team on one digital platform. ‍ ‍4) Privacy Is the Priority: There are no required social events. Our priority is providing privacy, a quiet environment, and security for all our guests. Our team will take care of cleaning the common spaces every week, so that our kitchen/dining areas are always comfortable. But if you want to expand your network or social circle, our office at WeWork offers you day/after-work communities. We just moved our headquarters to the newest WeWork offices in Long Island City, which is easily accessible by all subway lines. ‍5) 10 Years Perfecting the Co-Living Mindset: Our founder started this business in his apartment after he couldn’t find appropriately priced accommodation for his first three months in New York. But our whole team has experienced co-living firsthand, so we understand what the customer feels and will need next. “We live and breathe co-living: first as roommates, and now serving our co-living guests.” ‍ ‍6) A Sustainable Business Model in the Sharing Economy: We won’t invest in luxury buildings like hotels or event spaces. We rent existing empty apartments and townhouses from the owners, put IKEA-type furniture in, and list the clean rooms on multiple digital platforms. We grow by our operational profit base, which comes from guests being charged fair prices and the revenue owners receive. However, what drives our growth is not the number of rooms, but our deep understanding of how to care for guests and rooms 24/7, and the intangible value within them. ‍ ‍7) Our Vision - Making Dreams Come True: CrossOver’s goal is to help our guests achieve their goals and dreams by providing the most affordable and flexible housing environment available. But it doesn’t stop here. Our guests’ dreams are expanding to a variety of locations around the globe, and CrossOver will be right there with them—powering the dreams of residents, landlords, and our staff in the wider world.
 
164
Vibe is a full-service provider of furnished homes in New York City. Our team is here to help you find your space and to support you during your journey. We're always operating with your comfort in mind and we've taken care to plan for your arrival long before you turn the key. Our homes are fully furnished and equipped with everything you need for a perfect stay and are located in some of the best neighborhoods in Manhattan. Whatever you're into and wherever you want to stay, there's a Vibe space for you!
 
122
At Outpost Club, we believe that finding a place to live should be as easy as buying a cup of coffee. Founded in 2016 by a team who knows what it’s like to move we spent our careers traveling around the world, working remotely and building start-ups. Outpost Club was launched by three entrepreneurs who understands the challenges of moving to new places, working remotely and building a start-up from scratch in a new place. Our mission is to build a tight-knit community with shared passions and visions, thereby making the world we live in a better place. Apply today, move in tomorrow. Our spaces are cleaned regularly and restocked with all the essentials. Flexibility and convenience matched with beautiful spaces and new friends, that’s what we’re all about for the thousands of guests we’ve served.
 
119
Other values (15476)
21327 

Length

Max length7186
Median length202
Mean length340.7846896
Min length1

Characters and Unicode

Total characters7554515
Distinct characters998
Distinct categories21 ?
Distinct scripts10 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12992 ?
Unique (%)58.6%

Sample

1st rowA New Yorker since 2000! My passion is creating beautiful, unique spaces where unforgettable memories are made. It's my pleasure to host people from around the world and meet new faces. Welcome travelers! I am a Sound Therapy Practitioner and Kundalini Yoga & Meditation teacher. I work with energy and sound for relaxation and healing, using Symphonic gong, singing bowls, tuning forks, drums, voice and other instruments.
2nd rowLaid-back Native New Yorker (formerly bi-coastal) and AirBnb host of over 6 years and over 400 stays! Besides being a long-time and attentive AirBnb host, I am an actor, attorney, professor and group fitness instructor.
3rd row I am an artist(painter, filmmaker) and curator who is working in the film industry while I'm building my business. I am extremely easy going and would like that you are the laid back and enjoy life kind of person. I also ask that you are open, honest and easy to communicate with as this is how I like to live my life.And of course creative people are very welcome!
4th rowI used to work for a financial industry but now I work at a Japanese food market as an assistant manager.
5th rowWelcome to family life with my oldest two away at college all the way down to a seventh grader. You may see everything from lively dinner conversation to a nearly empty apartment with everyone out enjoying the city. I'm friendly, leave tea and coffee always available and responsive to a guest's needs. My family has enjoyed everything from the guest who tends towards the private as well as the ones who dive in with the science experiment! Hosting through Airbnb has created a wonderful opportunity to meet people from all over the world, plot their addresses, and learn about other places. I began hosting through Airbnb four years ago as a work-from-home job. I continue because the whole family entirely grooves on the notion we get to meet people from all over the world and help them visit our city.
ValueCountFrequency (%)
Why take a chance picking & choosing between so many individual hosts when you can enjoy the highest-quality guest experience from one consistent host -- Blueground. We are a global real estate tech company offering +3500 fully-equipped & furnished apartments for a month, a year or longer across 12 cities and 3 continents. Centrally-based in vibrant neighborhoods, each home is tech-powered & furnished by our expert Interior Design teams. Enjoy at-home amenities like high-speed WiFi, a fully-stocked kitchen, smart TV, premium bedding/towels, quality toiletries, and depending on the apartment choice -- artisan coffee, bluetooth speakers & select building amenities such as pools, gyms & outdoor spaces. From meal, wine & grocery delivery to laundry & dry-cleaning right to your door, our guests can choose from a number of service benefits. Each apartment is safe & professionally sanitized. During your stay Driven by a mission to help you show up & start living, Blueground is proud to host thousands of guests around the world in the following cities: New York, Los Angeles, San Francisco, Boston, Chicago, Washington D.C., Seattle, Dubai, Istanbul, Paris, London and Athens. Upon arrival, you’ll either be greeted personally by a Blueground team member or given self check-in instructions. The entire apartment is yours to enjoy; and for additional support, our Client Experience team is available via phone, email & our Guest App through which you can schedule additional cleanings, request fresh towels/linens, submit maintenance requests, and view neighborhood recommendations. We’ll share all details upon confirmation of your stay. 255
 
0.7%
At June Homes, our mission is to make renting an apartment as easy and stress-free as possible. We make applying simple and seamless, charge no hidden fees, and take care of the little things. All of our homes are fully furnished, and include Netflix/HBO, monthly delivery of home supplies, WiFi and utilities for $125-$200/month. If you have any issues, we’re available with 24-hour support. All of our apartments are available with flexible terms, meaning you can lease for 1–18 months. New to the city? Consider moving in for two months and then trying out a new neighborhood. Need a roommate? We also offer shared homes to our member-only community. Our design team ensures that each home meets our elevated standards, and you can select between furnished or unfurnished. It’s your call. It’s your home.181
 
0.5%
Dear Airbnb guests! I manage some co-living spaces in Manhattan, Queens, and Brooklyn with my team members. I have been managing shared apartments for a decade and had people from 74 different countries so far :) Please feel free to ask me any questions! *I can speak Japanese as well! Please feel free to contact me in Japanese if you do. Who we are: Our Principles 1) Growing Our Alumni Community: We don’t require membership fees to maximize our profits. Instead, our focus is on growing our alumni community. We believe that our services and fair pricing speak for themselves among our guests. Our alumni posted 200+ reviews in 2019. What’s more, 75% of the reviews gave us five stars and 97% awarded more than four stars. Our alumni community spans the globe with 74 unique nationalities, and it has been expanding mostly by word of mouth. We look forward to serving all our new guests: our alumni of tomorrow. ‍ ‍2) Transparency. One All-Inclusive Price. That’s What We’re About: There’s no math required. The price for our one-month minimum stay is simple and fair, no matter how long you stay with us. Our one-month price is already competitive (averaging $1,100 to $1,500, with 90% of our 150 rooms under $1,650 per month), compared to others’ discounted prices for three- to six-month stays. In 2019, 30%+ of our customers extended their original stay by a few months. There’s really no substitute for an all-inclusive co-living environment, with a furnished private room, that’s ready for you on day one. ‍ ‍3) Increasing Value for the Local Property Industry: We provide co-living communities for our guests by helping property owners draw more value from under-managed residential properties. We care about our customer community, of course, but we’re also excited about uniting property owners, vendors, and our team on one digital platform. ‍ ‍4) Privacy Is the Priority: There are no required social events. Our priority is providing privacy, a quiet environment, and security for all our guests. Our team will take care of cleaning the common spaces every week, so that our kitchen/dining areas are always comfortable. But if you want to expand your network or social circle, our office at WeWork offers you day/after-work communities. We just moved our headquarters to the newest WeWork offices in Long Island City, which is easily accessible by all subway lines. ‍5) 10 Years Perfecting the Co-Living Mindset: Our founder started this business in his apartment after he couldn’t find appropriately priced accommodation for his first three months in New York. But our whole team has experienced co-living firsthand, so we understand what the customer feels and will need next. “We live and breathe co-living: first as roommates, and now serving our co-living guests.” ‍ ‍6) A Sustainable Business Model in the Sharing Economy: We won’t invest in luxury buildings like hotels or event spaces. We rent existing empty apartments and townhouses from the owners, put IKEA-type furniture in, and list the clean rooms on multiple digital platforms. We grow by our operational profit base, which comes from guests being charged fair prices and the revenue owners receive. However, what drives our growth is not the number of rooms, but our deep understanding of how to care for guests and rooms 24/7, and the intangible value within them. ‍ ‍7) Our Vision - Making Dreams Come True: CrossOver’s goal is to help our guests achieve their goals and dreams by providing the most affordable and flexible housing environment available. But it doesn’t stop here. Our guests’ dreams are expanding to a variety of locations around the globe, and CrossOver will be right there with them—powering the dreams of residents, landlords, and our staff in the wider world.164
 
0.4%
Vibe is a full-service provider of furnished homes in New York City. Our team is here to help you find your space and to support you during your journey. We're always operating with your comfort in mind and we've taken care to plan for your arrival long before you turn the key. Our homes are fully furnished and equipped with everything you need for a perfect stay and are located in some of the best neighborhoods in Manhattan. Whatever you're into and wherever you want to stay, there's a Vibe space for you!122
 
0.3%
At Outpost Club, we believe that finding a place to live should be as easy as buying a cup of coffee. Founded in 2016 by a team who knows what it’s like to move we spent our careers traveling around the world, working remotely and building start-ups. Outpost Club was launched by three entrepreneurs who understands the challenges of moving to new places, working remotely and building a start-up from scratch in a new place. Our mission is to build a tight-knit community with shared passions and visions, thereby making the world we live in a better place. Apply today, move in tomorrow. Our spaces are cleaned regularly and restocked with all the essentials. Flexibility and convenience matched with beautiful spaces and new friends, that’s what we’re all about for the thousands of guests we’ve served. 119
 
0.3%
I work for Furnished Quarters, the largest provider of furnished apartments in the Northeast. My family started this business over 20 years ago and we welcome the opportunity to host you in our apartments. Guests can expect a comfortable, fully furnished and equipped private apartment, plenty of helpful neighborhood information and 24-hour access to our team. We consider ourselves first and foremost a hospitality company and we are here to provide a worry-free stay that enables you to enjoy the city and feel like a local from the moment you arrive. 88
 
0.2%
At Outpost Club, we believe that finding a place to live should be as easy as buying a cup of coffee. Founded in 2016 by a team who knows what it’s like to move we spent our careers traveling around the world, working remotely and building start-ups. Outpost Club was launched by three entrepreneurs who understands the challenges of moving to new places, working remotely and building a start-up from scratch in a new place. Our mission is to build a tight-knit community with shared passions and visions, thereby making the world we live in a better place. Apply today, move in tomorrow. Our spaces are cleaned regularly and restocked with all the essentials. Flexibility and convenience matched with beautiful spaces and new friends, that’s what we’re all about for the thousands of guests we’ve served. 84
 
0.2%
We have been providing vacation rental apartments for over 10 years across the East Coast. We are known for our distinctively furnished apartments in popular locations, and for our attentive service. You’ll find that our rates are quite reasonable. If you're looking for a safe, comfortable place with fabulous amenities and Wi-Fi (we know you need the Wi-Fi!) in the Boston MA area, Washington DC, Miami FL or very close to NYC in Jersey City or Hoboken, we'd love to host you. Many of the buildings where our apartments are located feature amenities such as beautiful lobbies, 24 hour front desk staff, fitness centers, business centers, recreation rooms, indoor or outdoor pools and whirlpools. If you are traveling with children, some buildings offer playgrounds (many buildings are near public playgrounds as well) or indoor playrooms. Depending on the location, you can stay for just a few days, a week, a month or more. We offer an assortment of short-term apartments in sizes ranging from a studio to three bedrooms that are fully furnished with all the comforts of home. Our local staff meticulously prepares your apartment before your arrival, and we offer 24 hour assistance for any emergencies after business hours. When you arrive at your apartment, the beds will be made, towels and bath amenities will be stocked in the bathrooms, and the coffee maker will be set up in the kitchen with some sample coffees, sweetener and creamer (teabags too if that is your preference) to start your morning off properly. If you’d like to cook a meal, the kitchen is stocked with dishes, cutlery, glassware and pots and pans. The living room is set up with a TV and cable channels, and the Wi-Fi router password and instructions will be prominently displayed so you can get connected quickly. You can also make local and toll-free phone calls at no charge. Please contact us to confirm the exact availability of the apartment you are interested in. We’d love to host you (and your family) for your vacation or business trip. 76
 
0.2%
Reservations Manager, Murray Hill East Suites73
 
0.2%
At Outpost Club, we believe that finding a place to live should be as easy as buying a cup of coffee. Founded in 2016 by a team who knows what it’s like to move we spent our careers traveling around the world, working remotely and building start-ups. Outpost Club was launched by three entrepreneurs who understands the challenges of moving to new places, working remotely and building a start-up from scratch in a new place. Our mission is to build a tight-knit community with shared passions and visions, thereby making the world we live in a better place. Apply today, move in tomorrow. Our spaces are cleaned regularly and restocked with all the essentials. Flexibility and convenience matched with beautiful spaces and new friends, that’s what we’re all about for the thousands of guests we’ve served. 58
 
0.2%
Other values (15471)20948
56.6%
(Missing)14844
40.1%
2021-04-12T21:32:42.017343image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and61658
 
4.7%
to38315
 
2.9%
the36806
 
2.8%
i36345
 
2.8%
a34392
 
2.6%
in31169
 
2.4%
of19976
 
1.5%
my15723
 
1.2%
our15117
 
1.2%
for15033
 
1.1%
Other values (25096)1008913
76.8%

Most occurring characters

ValueCountFrequency (%)
1299107
17.2%
e679188
 
9.0%
a480790
 
6.4%
o474080
 
6.3%
t437360
 
5.8%
n432191
 
5.7%
i400085
 
5.3%
r380716
 
5.0%
s331506
 
4.4%
l264419
 
3.5%
Other values (988)2375073
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5640509
74.7%
Space Separator1299235
 
17.2%
Uppercase Letter267959
 
3.5%
Other Punctuation207059
 
2.7%
Control55647
 
0.7%
Decimal Number35297
 
0.5%
Dash Punctuation18731
 
0.2%
Final Punctuation8644
 
0.1%
Close Punctuation6692
 
0.1%
Other Letter4858
 
0.1%
Other values (11)9884
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
179
 
3.7%
175
 
3.6%
86
 
1.8%
80
 
1.6%
79
 
1.6%
58
 
1.2%
56
 
1.2%
50
 
1.0%
49
 
1.0%
48
 
1.0%
Other values (750)3998
82.3%
ValueCountFrequency (%)
e679188
12.0%
a480790
 
8.5%
o474080
 
8.4%
t437360
 
7.8%
n432191
 
7.7%
i400085
 
7.1%
r380716
 
6.7%
s331506
 
5.9%
l264419
 
4.7%
d201955
 
3.6%
Other values (91)1558219
27.6%
ValueCountFrequency (%)
I54633
20.4%
N18448
 
6.9%
C18305
 
6.8%
A17769
 
6.6%
W16664
 
6.2%
Y15866
 
5.9%
B12733
 
4.8%
M12502
 
4.7%
S12039
 
4.5%
T11779
 
4.4%
Other values (42)77221
28.8%
ValueCountFrequency (%)
,81564
39.4%
.79994
38.6%
'13963
 
6.7%
!12225
 
5.9%
:5512
 
2.7%
&4267
 
2.1%
/4046
 
2.0%
"1639
 
0.8%
;1144
 
0.6%
*828
 
0.4%
Other values (13)1877
 
0.9%
ValueCountFrequency (%)
®40
51.9%
22
28.6%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
1
 
1.3%
1
 
1.3%
1
 
1.3%
1
 
1.3%
ValueCountFrequency (%)
08010
22.7%
16550
18.6%
25974
16.9%
53221
9.1%
32961
 
8.4%
42645
 
7.5%
71868
 
5.3%
91579
 
4.5%
61372
 
3.9%
81117
 
3.2%
ValueCountFrequency (%)
|996
44.7%
+995
44.6%
>82
 
3.7%
~73
 
3.3%
=62
 
2.8%
<17
 
0.8%
3
 
0.1%
2
 
0.1%
ValueCountFrequency (%)
-18172
97.0%
300
 
1.6%
252
 
1.3%
7
 
< 0.1%
ValueCountFrequency (%)
12
48.0%
9
36.0%
2
 
8.0%
2
 
8.0%
ValueCountFrequency (%)
1299107
> 99.9%
 116
 
< 0.1%
12
 
< 0.1%
ValueCountFrequency (%)
392
82.5%
82
 
17.3%
«1
 
0.2%
ValueCountFrequency (%)
8244
95.4%
399
 
4.6%
»1
 
< 0.1%
ValueCountFrequency (%)
^71
74.7%
`13
 
13.7%
´11
 
11.6%
ValueCountFrequency (%)
1804
99.6%
7
 
0.4%
1
 
0.1%
ValueCountFrequency (%)
38171
68.6%
17476
31.4%
ValueCountFrequency (%)
(3937
99.6%
[17
 
0.4%
ValueCountFrequency (%)
)6671
99.7%
]21
 
0.3%
ValueCountFrequency (%)
$1135
100.0%
ValueCountFrequency (%)
_30
100.0%
ValueCountFrequency (%)
40
100.0%
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5906063
78.2%
Common1639343
 
21.7%
Han4384
 
0.1%
Cyrillic2368
 
< 0.1%
Inherited1844
 
< 0.1%
Hiragana332
 
< 0.1%
Katakana89
 
< 0.1%
Hangul47
 
< 0.1%
Georgian37
 
< 0.1%
Arabic8
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
179
 
4.1%
175
 
4.0%
86
 
2.0%
80
 
1.8%
79
 
1.8%
58
 
1.3%
56
 
1.3%
50
 
1.1%
49
 
1.1%
48
 
1.1%
Other values (642)3524
80.4%
ValueCountFrequency (%)
1299107
79.2%
,81564
 
5.0%
.79994
 
4.9%
38171
 
2.3%
-18172
 
1.1%
17476
 
1.1%
'13963
 
0.9%
!12225
 
0.7%
8244
 
0.5%
08010
 
0.5%
Other values (72)62417
 
3.8%
ValueCountFrequency (%)
e679188
 
11.5%
a480790
 
8.1%
o474080
 
8.0%
t437360
 
7.4%
n432191
 
7.3%
i400085
 
6.8%
r380716
 
6.4%
s331506
 
5.6%
l264419
 
4.5%
d201955
 
3.4%
Other values (71)1823773
30.9%
ValueCountFrequency (%)
о240
 
10.1%
е199
 
8.4%
а165
 
7.0%
т156
 
6.6%
и151
 
6.4%
н138
 
5.8%
с136
 
5.7%
р112
 
4.7%
в106
 
4.5%
у91
 
3.8%
Other values (44)874
36.9%
ValueCountFrequency (%)
30
 
9.0%
26
 
7.8%
22
 
6.6%
21
 
6.3%
16
 
4.8%
16
 
4.8%
15
 
4.5%
14
 
4.2%
12
 
3.6%
10
 
3.0%
Other values (33)150
45.2%
ValueCountFrequency (%)
9
 
10.1%
7
 
7.9%
6
 
6.7%
5
 
5.6%
5
 
5.6%
5
 
5.6%
5
 
5.6%
4
 
4.5%
3
 
3.4%
3
 
3.4%
Other values (24)37
41.6%
ValueCountFrequency (%)
4
 
8.5%
4
 
8.5%
3
 
6.4%
3
 
6.4%
3
 
6.4%
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
Other values (19)19
40.4%
ValueCountFrequency (%)
5
13.5%
4
10.8%
4
10.8%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (8)8
21.6%
ValueCountFrequency (%)
م4
50.0%
س2
25.0%
ل2
25.0%
ValueCountFrequency (%)
1804
97.8%
40
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII7534280
99.7%
Punctuation11616
 
0.2%
CJK4382
 
0.1%
Cyrillic2368
 
< 0.1%
None1365
 
< 0.1%
Hiragana332
 
< 0.1%
Hangul47
 
< 0.1%
VS40
 
< 0.1%
Georgian37
 
< 0.1%
Dingbats27
 
< 0.1%
Other values (3)21
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
1299107
17.2%
e679188
 
9.0%
a480790
 
6.4%
o474080
 
6.3%
t437360
 
5.8%
n432191
 
5.7%
i400085
 
5.3%
r380716
 
5.1%
s331506
 
4.4%
l264419
 
3.5%
Other values (85)2354838
31.3%
ValueCountFrequency (%)
8244
71.0%
1804
 
15.5%
399
 
3.4%
392
 
3.4%
300
 
2.6%
252
 
2.2%
82
 
0.7%
65
 
0.6%
37
 
0.3%
12
 
0.1%
Other values (6)29
 
0.2%
ValueCountFrequency (%)
é284
20.8%
170
12.5%
 116
 
8.5%
ñ112
 
8.2%
í66
 
4.8%
á64
 
4.7%
ç62
 
4.5%
à54
 
4.0%
ó51
 
3.7%
44
 
3.2%
Other values (67)342
25.1%
ValueCountFrequency (%)
22
81.5%
2
 
7.4%
2
 
7.4%
1
 
3.7%
ValueCountFrequency (%)
3
30.0%
3
30.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
ValueCountFrequency (%)
179
 
4.1%
175
 
4.0%
86
 
2.0%
80
 
1.8%
79
 
1.8%
58
 
1.3%
56
 
1.3%
50
 
1.1%
49
 
1.1%
48
 
1.1%
Other values (641)3522
80.4%
ValueCountFrequency (%)
40
100.0%
ValueCountFrequency (%)
م4
50.0%
س2
25.0%
ل2
25.0%
ValueCountFrequency (%)
30
 
9.0%
26
 
7.8%
22
 
6.6%
21
 
6.3%
16
 
4.8%
16
 
4.8%
15
 
4.5%
14
 
4.2%
12
 
3.6%
10
 
3.0%
Other values (33)150
45.2%
ValueCountFrequency (%)
3
100.0%
ValueCountFrequency (%)
о240
 
10.1%
е199
 
8.4%
а165
 
7.0%
т156
 
6.6%
и151
 
6.4%
н138
 
5.8%
с136
 
5.7%
р112
 
4.7%
в106
 
4.5%
у91
 
3.8%
Other values (44)874
36.9%
ValueCountFrequency (%)
4
 
8.5%
4
 
8.5%
3
 
6.4%
3
 
6.4%
3
 
6.4%
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
Other values (19)19
40.4%
ValueCountFrequency (%)
5
13.5%
4
10.8%
4
10.8%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (8)8
21.6%

host_response_time
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing18507
Missing (%)50.0%
Memory size289.3 KiB
within an hour
10143 
within a few hours
3937 
within a day
3039 
a few days or more
1386 

Length

Max length18
Median length14
Mean length14.82215617
Min length12

Characters and Unicode

Total characters274284
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowwithin a few hours
2nd rowwithin a few hours
3rd rowwithin a day
4th rowwithin an hour
5th rowwithin an hour
ValueCountFrequency (%)
within an hour10143
27.4%
within a few hours3937
 
10.6%
within a day3039
 
8.2%
a few days or more1386
 
3.7%
(Missing)18507
50.0%
2021-04-12T21:32:42.274387image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-04-12T21:32:42.349430image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
within17119
27.5%
hour10143
16.3%
an10143
16.3%
a8362
13.4%
few5323
 
8.6%
hours3937
 
6.3%
day3039
 
4.9%
days1386
 
2.2%
more1386
 
2.2%
or1386
 
2.2%

Most occurring characters

ValueCountFrequency (%)
43719
15.9%
i34238
12.5%
h31199
11.4%
n27262
9.9%
a22930
8.4%
w22442
8.2%
t17119
 
6.2%
o16852
 
6.1%
r16852
 
6.1%
u14080
 
5.1%
Other values (6)27591
10.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter230565
84.1%
Space Separator43719
 
15.9%

Most frequent character per category

ValueCountFrequency (%)
i34238
14.8%
h31199
13.5%
n27262
11.8%
a22930
9.9%
w22442
9.7%
t17119
7.4%
o16852
7.3%
r16852
7.3%
u14080
6.1%
e6709
 
2.9%
Other values (5)20882
9.1%
ValueCountFrequency (%)
43719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin230565
84.1%
Common43719
 
15.9%

Most frequent character per script

ValueCountFrequency (%)
i34238
14.8%
h31199
13.5%
n27262
11.8%
a22930
9.9%
w22442
9.7%
t17119
7.4%
o16852
7.3%
r16852
7.3%
u14080
6.1%
e6709
 
2.9%
Other values (5)20882
9.1%
ValueCountFrequency (%)
43719
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII274284
100.0%

Most frequent character per block

ValueCountFrequency (%)
43719
15.9%
i34238
12.5%
h31199
11.4%
n27262
9.9%
a22930
8.4%
w22442
8.2%
t17119
 
6.2%
o16852
 
6.1%
r16852
 
6.1%
u14080
 
5.1%
Other values (6)27591
10.1%

host_response_rate
Real number (ℝ≥0)

MISSING
ZEROS

Distinct77
Distinct (%)0.4%
Missing18507
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean88.52558768
Minimum0
Maximum100
Zeros930
Zeros (%)2.5%
Memory size289.3 KiB
2021-04-12T21:32:42.455147image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q190
median100
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)10

Descriptive statistics

Standard deviation25.02346514
Coefficient of variation (CV)0.2826692914
Kurtosis5.952935932
Mean88.52558768
Median Absolute Deviation (MAD)0
Skewness-2.617534006
Sum1638166
Variance626.1738075
MonotocityNot monotonic
2021-04-12T21:32:42.605714image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10011869
32.1%
0930
 
2.5%
90774
 
2.1%
80509
 
1.4%
96374
 
1.0%
95344
 
0.9%
50341
 
0.9%
94265
 
0.7%
93224
 
0.6%
67216
 
0.6%
Other values (67)2659
 
7.2%
(Missing)18507
50.0%
ValueCountFrequency (%)
0930
2.5%
41
 
< 0.1%
51
 
< 0.1%
87
 
< 0.1%
91
 
< 0.1%
ValueCountFrequency (%)
10011869
32.1%
99190
 
0.5%
98150
 
0.4%
9798
 
0.3%
96374
 
1.0%

host_acceptance_rate
Real number (ℝ≥0)

MISSING
ZEROS

Distinct98
Distinct (%)0.4%
Missing14633
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean80.47124536
Minimum0
Maximum100
Zeros1401
Zeros (%)3.8%
Memory size289.3 KiB
2021-04-12T21:32:42.750702image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q173
median94
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)27

Descriptive statistics

Standard deviation28.08515695
Coefficient of variation (CV)0.3490086033
Kurtosis2.012175337
Mean80.47124536
Median Absolute Deviation (MAD)6
Skewness-1.712531394
Sum1800866
Variance788.776041
MonotocityNot monotonic
2021-04-12T21:32:42.895530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1007358
19.9%
01401
 
3.8%
99974
 
2.6%
50773
 
2.1%
98729
 
2.0%
94654
 
1.8%
97593
 
1.6%
92592
 
1.6%
67505
 
1.4%
96483
 
1.3%
Other values (88)8317
22.5%
(Missing)14633
39.5%
ValueCountFrequency (%)
01401
3.8%
25
 
< 0.1%
41
 
< 0.1%
51
 
< 0.1%
64
 
< 0.1%
ValueCountFrequency (%)
1007358
19.9%
99974
 
2.6%
98729
 
2.0%
97593
 
1.6%
96483
 
1.3%
Distinct2
Distinct (%)< 0.1%
Missing18
Missing (%)< 0.1%
Memory size72.4 KiB
False
30023 
True
6971 
(Missing)
 
18
ValueCountFrequency (%)
False30023
81.1%
True6971
 
18.8%
(Missing)18
 
< 0.1%
2021-04-12T21:32:42.986579image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

host_total_listings_count
Real number (ℝ≥0)

ZEROS

Distinct79
Distinct (%)0.2%
Missing18
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean23.97415797
Minimum0
Maximum2739
Zeros4501
Zeros (%)12.2%
Memory size289.3 KiB
2021-04-12T21:32:43.073566image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile39
Maximum2739
Range2739
Interquartile range (IQR)1

Descriptive statistics

Standard deviation158.2248598
Coefficient of variation (CV)6.599808842
Kurtosis99.9454809
Mean23.97415797
Median Absolute Deviation (MAD)1
Skewness9.543009415
Sum886900
Variance25035.10624
MonotocityNot monotonic
2021-04-12T21:32:43.205874image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
118246
49.3%
25198
 
14.0%
04501
 
12.2%
32136
 
5.8%
41165
 
3.1%
5700
 
1.9%
6481
 
1.3%
7431
 
1.2%
8312
 
0.8%
1337255
 
0.7%
Other values (69)3569
 
9.6%
ValueCountFrequency (%)
04501
 
12.2%
118246
49.3%
25198
 
14.0%
32136
 
5.8%
41165
 
3.1%
ValueCountFrequency (%)
273913
 
< 0.1%
18275
 
< 0.1%
181366
0.2%
15156
 
< 0.1%
14497
 
< 0.1%

host_verifications
Categorical

HIGH CARDINALITY

Distinct524
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
['email', 'phone', 'reviews', 'kba']
3031 
['email', 'phone', 'reviews', 'jumio', 'government_id']
2749 
['email', 'phone']
2727 
['email', 'phone', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']
 
2389
['email', 'phone', 'reviews']
 
1721
Other values (519)
24395 

Length

Max length177
Median length67
Mean length66.21066141
Min length2

Characters and Unicode

Total characters2450589
Distinct characters31
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)0.4%

Sample

1st row['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'selfie', 'government_id', 'identity_manual', 'work_email']
2nd row['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'government_id']
3rd row['email', 'phone', 'facebook', 'reviews', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']
4th row['email', 'phone', 'facebook', 'reviews']
5th row['email', 'phone', 'facebook', 'google', 'reviews', 'jumio', 'government_id']
ValueCountFrequency (%)
['email', 'phone', 'reviews', 'kba']3031
 
8.2%
['email', 'phone', 'reviews', 'jumio', 'government_id']2749
 
7.4%
['email', 'phone']2727
 
7.4%
['email', 'phone', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']2389
 
6.5%
['email', 'phone', 'reviews']1721
 
4.6%
['email', 'phone', 'offline_government_id', 'government_id']1490
 
4.0%
['email', 'phone', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']1393
 
3.8%
['email', 'phone', 'reviews', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']1328
 
3.6%
['email', 'phone', 'reviews', 'jumio', 'offline_government_id', 'government_id']1108
 
3.0%
['email', 'phone', 'facebook', 'reviews', 'kba']1065
 
2.9%
Other values (514)18011
48.7%
2021-04-12T21:32:43.520529image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
phone36821
18.7%
email34071
17.3%
government_id24327
12.3%
reviews23688
12.0%
offline_government_id17416
8.8%
jumio15484
7.9%
selfie11625
 
5.9%
identity_manual10394
 
5.3%
kba8200
 
4.2%
facebook7145
 
3.6%
Other values (11)7912
 
4.0%

Most occurring characters

ValueCountFrequency (%)
'394106
16.1%
e267929
 
10.9%
i171081
 
7.0%
n160546
 
6.6%
,160071
 
6.5%
160071
 
6.5%
o135183
 
5.5%
m107886
 
4.4%
l82129
 
3.4%
a77231
 
3.2%
Other values (21)734356
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1586555
64.7%
Other Punctuation554177
 
22.6%
Space Separator160071
 
6.5%
Connector Punctuation75780
 
3.1%
Open Punctuation36994
 
1.5%
Close Punctuation36994
 
1.5%
Uppercase Letter18
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
e267929
16.9%
i171081
10.8%
n160546
10.1%
o135183
 
8.5%
m107886
 
6.8%
l82129
 
5.2%
a77231
 
4.9%
r70740
 
4.5%
v65431
 
4.1%
t62582
 
3.9%
Other values (14)385817
24.3%
ValueCountFrequency (%)
'394106
71.1%
,160071
28.9%
ValueCountFrequency (%)
[36994
100.0%
ValueCountFrequency (%)
160071
100.0%
ValueCountFrequency (%)
_75780
100.0%
ValueCountFrequency (%)
]36994
100.0%
ValueCountFrequency (%)
N18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1586573
64.7%
Common864016
35.3%

Most frequent character per script

ValueCountFrequency (%)
e267929
16.9%
i171081
10.8%
n160546
10.1%
o135183
 
8.5%
m107886
 
6.8%
l82129
 
5.2%
a77231
 
4.9%
r70740
 
4.5%
v65431
 
4.1%
t62582
 
3.9%
Other values (15)385835
24.3%
ValueCountFrequency (%)
'394106
45.6%
,160071
18.5%
160071
18.5%
_75780
 
8.8%
[36994
 
4.3%
]36994
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2450589
100.0%

Most frequent character per block

ValueCountFrequency (%)
'394106
16.1%
e267929
 
10.9%
i171081
 
7.0%
n160546
 
6.6%
,160071
 
6.5%
160071
 
6.5%
o135183
 
5.5%
m107886
 
4.4%
l82129
 
3.4%
a77231
 
3.2%
Other values (21)734356
30.0%
Distinct2
Distinct (%)< 0.1%
Missing18
Missing (%)< 0.1%
Memory size72.4 KiB
True
36882 
False
 
112
(Missing)
 
18
ValueCountFrequency (%)
True36882
99.6%
False112
 
0.3%
(Missing)18
 
< 0.1%
2021-04-12T21:32:43.618032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing18
Missing (%)< 0.1%
Memory size72.4 KiB
True
29590 
False
7404 
(Missing)
 
18
ValueCountFrequency (%)
True29590
79.9%
False7404
 
20.0%
(Missing)18
 
< 0.1%
2021-04-12T21:32:43.656021image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

neighbourhood_cleansed
Categorical

HIGH CARDINALITY

Distinct220
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
Williamsburg
2733 
Bedford-Stuyvesant
2711 
Harlem
 
1972
Bushwick
 
1678
Hell's Kitchen
 
1506
Other values (215)
26412 

Length

Max length25
Median length12
Mean length11.78787961
Min length4

Characters and Unicode

Total characters436293
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowMidtown
2nd rowClinton Hill
3rd rowBedford-Stuyvesant
4th rowMidtown
5th rowUpper West Side
ValueCountFrequency (%)
Williamsburg2733
 
7.4%
Bedford-Stuyvesant2711
 
7.3%
Harlem1972
 
5.3%
Bushwick1678
 
4.5%
Hell's Kitchen1506
 
4.1%
Upper West Side1454
 
3.9%
Midtown1451
 
3.9%
Upper East Side1342
 
3.6%
East Village1314
 
3.6%
Crown Heights1127
 
3.0%
Other values (210)19724
53.3%
2021-04-12T21:32:43.899312image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
east4815
 
8.1%
side3503
 
5.9%
upper2796
 
4.7%
williamsburg2733
 
4.6%
bedford-stuyvesant2711
 
4.5%
harlem2700
 
4.5%
heights2622
 
4.4%
village2302
 
3.9%
west2072
 
3.5%
bushwick1678
 
2.8%
Other values (233)31789
53.2%

Most occurring characters

ValueCountFrequency (%)
e40280
 
9.2%
i31720
 
7.3%
s29601
 
6.8%
t29224
 
6.7%
a28090
 
6.4%
l25515
 
5.8%
r25059
 
5.7%
22709
 
5.2%
n19676
 
4.5%
o18576
 
4.3%
Other values (43)165843
38.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter345656
79.2%
Uppercase Letter63239
 
14.5%
Space Separator22709
 
5.2%
Dash Punctuation3073
 
0.7%
Other Punctuation1616
 
0.4%

Most frequent character per category

ValueCountFrequency (%)
e40280
11.7%
i31720
 
9.2%
s29601
 
8.6%
t29224
 
8.5%
a28090
 
8.1%
l25515
 
7.4%
r25059
 
7.2%
n19676
 
5.7%
o18576
 
5.4%
d15274
 
4.4%
Other values (15)82641
23.9%
ValueCountFrequency (%)
H8857
14.0%
S8603
13.6%
B6170
9.8%
W6085
9.6%
E5276
 
8.3%
C4031
 
6.4%
U2849
 
4.5%
G2699
 
4.3%
M2622
 
4.1%
F2410
 
3.8%
Other values (14)13637
21.6%
ValueCountFrequency (%)
'1510
93.4%
.106
 
6.6%
ValueCountFrequency (%)
22709
100.0%
ValueCountFrequency (%)
-3073
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin408895
93.7%
Common27398
 
6.3%

Most frequent character per script

ValueCountFrequency (%)
e40280
 
9.9%
i31720
 
7.8%
s29601
 
7.2%
t29224
 
7.1%
a28090
 
6.9%
l25515
 
6.2%
r25059
 
6.1%
n19676
 
4.8%
o18576
 
4.5%
d15274
 
3.7%
Other values (39)145880
35.7%
ValueCountFrequency (%)
22709
82.9%
-3073
 
11.2%
'1510
 
5.5%
.106
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII436293
100.0%

Most frequent character per block

ValueCountFrequency (%)
e40280
 
9.2%
i31720
 
7.3%
s29601
 
6.8%
t29224
 
6.7%
a28090
 
6.4%
l25515
 
5.8%
r25059
 
5.7%
22709
 
5.2%
n19676
 
4.5%
o18576
 
4.3%
Other values (43)165843
38.0%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
Manhattan
16553 
Brooklyn
14474 
Queens
4704 
Bronx
 
992
Staten Island
 
289

Length

Max length13
Median length8
Mean length8.151680536
Min length5

Characters and Unicode

Total characters301710
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowBrooklyn
3rd rowBrooklyn
4th rowManhattan
5th rowManhattan
ValueCountFrequency (%)
Manhattan16553
44.7%
Brooklyn14474
39.1%
Queens4704
 
12.7%
Bronx992
 
2.7%
Staten Island289
 
0.8%
2021-04-12T21:32:44.151291image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-04-12T21:32:44.233300image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
manhattan16553
44.4%
brooklyn14474
38.8%
queens4704
 
12.6%
bronx992
 
2.7%
staten289
 
0.8%
island289
 
0.8%

Most occurring characters

ValueCountFrequency (%)
n53854
17.8%
a50237
16.7%
t33684
11.2%
o29940
9.9%
M16553
 
5.5%
h16553
 
5.5%
B15466
 
5.1%
r15466
 
5.1%
l14763
 
4.9%
k14474
 
4.8%
Other values (10)40720
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter264120
87.5%
Uppercase Letter37301
 
12.4%
Space Separator289
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
n53854
20.4%
a50237
19.0%
t33684
12.8%
o29940
11.3%
h16553
 
6.3%
r15466
 
5.9%
l14763
 
5.6%
k14474
 
5.5%
y14474
 
5.5%
e9697
 
3.7%
Other values (4)10978
 
4.2%
ValueCountFrequency (%)
M16553
44.4%
B15466
41.5%
Q4704
 
12.6%
S289
 
0.8%
I289
 
0.8%
ValueCountFrequency (%)
289
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin301421
99.9%
Common289
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
n53854
17.9%
a50237
16.7%
t33684
11.2%
o29940
9.9%
M16553
 
5.5%
h16553
 
5.5%
B15466
 
5.1%
r15466
 
5.1%
l14763
 
4.9%
k14474
 
4.8%
Other values (9)40431
13.4%
ValueCountFrequency (%)
289
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII301710
100.0%

Most frequent character per block

ValueCountFrequency (%)
n53854
17.8%
a50237
16.7%
t33684
11.2%
o29940
9.9%
M16553
 
5.5%
h16553
 
5.5%
B15466
 
5.1%
r15466
 
5.1%
l14763
 
4.9%
k14474
 
4.8%
Other values (10)40720
13.5%

latitude
Real number (ℝ≥0)

Distinct17044
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.72965328
Minimum40.50868
Maximum40.91214
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:44.354347image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum40.50868
5-th percentile40.6448255
Q140.69032
median40.725465
Q340.76248
95-th percentile40.8262445
Maximum40.91214
Range0.40346
Interquartile range (IQR)0.07216

Descriptive statistics

Standard deviation0.05471032054
Coefficient of variation (CV)0.001343255249
Kurtosis0.1861640964
Mean40.72965328
Median Absolute Deviation (MAD)0.03614
Skewness0.2116456618
Sum1507485.927
Variance0.002993219174
MonotocityNot monotonic
2021-04-12T21:32:44.496300image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.7436161
 
0.2%
40.7641138
 
0.1%
40.7607628
 
0.1%
40.7157925
 
0.1%
40.7468419
 
0.1%
40.7543619
 
0.1%
40.7189919
 
0.1%
40.7462318
 
< 0.1%
40.7004818
 
< 0.1%
40.7375617
 
< 0.1%
Other values (17034)36750
99.3%
ValueCountFrequency (%)
40.508681
< 0.1%
40.520741
< 0.1%
40.530811
< 0.1%
40.537621
< 0.1%
40.539121
< 0.1%
ValueCountFrequency (%)
40.912141
< 0.1%
40.911271
< 0.1%
40.910781
< 0.1%
40.910151
< 0.1%
40.909841
< 0.1%

longitude
Real number (ℝ)

Distinct13557
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-73.95098882
Minimum-74.23986
Maximum-73.71087
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:44.665335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-74.23986
5-th percentile-74.0040545
Q1-73.9838125
median-73.95579
Q3-73.93372
95-th percentile-73.8569955
Maximum-73.71087
Range0.52899
Interquartile range (IQR)0.0500925

Descriptive statistics

Standard deviation0.04829055915
Coefficient of variation (CV)-0.0006530076192
Kurtosis4.332554029
Mean-73.95098882
Median Absolute Deviation (MAD)0.0262
Skewness1.331141328
Sum-2737073.998
Variance0.002331978103
MonotocityNot monotonic
2021-04-12T21:32:44.818002image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-73.9724968
 
0.2%
-73.9937139
 
0.1%
-73.9861133
 
0.1%
-73.9939123
 
0.1%
-74.0058823
 
0.1%
-73.953522
 
0.1%
-73.9764320
 
0.1%
-73.9967520
 
0.1%
-73.9197720
 
0.1%
-73.9977319
 
0.1%
Other values (13547)36725
99.2%
ValueCountFrequency (%)
-74.239861
< 0.1%
-74.208821
< 0.1%
-74.201361
< 0.1%
-74.197411
< 0.1%
-74.182391
< 0.1%
ValueCountFrequency (%)
-73.710871
< 0.1%
-73.712991
< 0.1%
-73.717221
< 0.1%
-73.720541
< 0.1%
-73.721541
< 0.1%

property_type
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct75
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
Entire apartment
15506 
Private room in apartment
12037 
Private room in house
1897 
Private room in townhouse
 
1044
Entire condominium
 
983
Other values (70)
5545 

Length

Max length34
Median length18
Mean length19.82338161
Min length3

Characters and Unicode

Total characters733703
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowEntire apartment
2nd rowEntire guest suite
3rd rowPrivate room in apartment
4th rowPrivate room in apartment
5th rowPrivate room in apartment
ValueCountFrequency (%)
Entire apartment15506
41.9%
Private room in apartment12037
32.5%
Private room in house1897
 
5.1%
Private room in townhouse1044
 
2.8%
Entire condominium983
 
2.7%
Entire house949
 
2.6%
Entire loft628
 
1.7%
Entire townhouse589
 
1.6%
Shared room in apartment501
 
1.4%
Private room in condominium477
 
1.3%
Other values (65)2401
 
6.5%
2021-04-12T21:32:45.150352image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
apartment28432
25.9%
entire19317
17.6%
room17655
16.1%
in17634
16.1%
private16162
14.7%
house2954
 
2.7%
townhouse1641
 
1.5%
condominium1481
 
1.4%
loft1017
 
0.9%
hotel707
 
0.6%
Other values (39)2621
 
2.4%

Most occurring characters

ValueCountFrequency (%)
t97098
13.2%
r82048
11.2%
a74090
10.1%
72609
9.9%
e72150
9.8%
n70079
9.6%
i57185
7.8%
m49074
6.7%
o46878
6.4%
p28541
 
3.9%
Other values (26)83951
11.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter624025
85.1%
Space Separator72609
 
9.9%
Uppercase Letter37046
 
5.0%
Other Punctuation22
 
< 0.1%
Dash Punctuation1
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
t97098
15.6%
r82048
13.1%
a74090
11.9%
e72150
11.6%
n70079
11.2%
i57185
9.2%
m49074
7.9%
o46878
7.5%
p28541
 
4.6%
v16574
 
2.7%
Other values (13)30308
 
4.9%
ValueCountFrequency (%)
E19317
52.1%
P16162
43.6%
R824
 
2.2%
S686
 
1.9%
C19
 
0.1%
V17
 
< 0.1%
T8
 
< 0.1%
B7
 
< 0.1%
H5
 
< 0.1%
L1
 
< 0.1%
ValueCountFrequency (%)
72609
100.0%
ValueCountFrequency (%)
/22
100.0%
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin661071
90.1%
Common72632
 
9.9%

Most frequent character per script

ValueCountFrequency (%)
t97098
14.7%
r82048
12.4%
a74090
11.2%
e72150
10.9%
n70079
10.6%
i57185
8.7%
m49074
7.4%
o46878
7.1%
p28541
 
4.3%
E19317
 
2.9%
Other values (23)64611
9.8%
ValueCountFrequency (%)
72609
> 99.9%
/22
 
< 0.1%
-1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII733703
100.0%

Most frequent character per block

ValueCountFrequency (%)
t97098
13.2%
r82048
11.2%
a74090
10.1%
72609
9.9%
e72150
9.8%
n70079
9.6%
i57185
7.8%
m49074
6.7%
o46878
6.4%
p28541
 
3.9%
Other values (26)83951
11.4%

room_type
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
Entire home/apt
19397 
Private room
16630 
Shared room
 
686
Hotel room
 
299

Length

Max length15
Median length15
Mean length13.53752837
Min length10

Characters and Unicode

Total characters501051
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEntire home/apt
2nd rowEntire home/apt
3rd rowPrivate room
4th rowPrivate room
5th rowPrivate room
ValueCountFrequency (%)
Entire home/apt19397
52.4%
Private room16630
44.9%
Shared room686
 
1.9%
Hotel room299
 
0.8%
2021-04-12T21:32:45.417424image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-04-12T21:32:45.497946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
home/apt19397
26.2%
entire19397
26.2%
room17615
23.8%
private16630
22.5%
shared686
 
0.9%
hotel299
 
0.4%

Most occurring characters

ValueCountFrequency (%)
e56409
11.3%
t55723
11.1%
o54926
11.0%
r54328
10.8%
37012
 
7.4%
m37012
 
7.4%
a36713
 
7.3%
i36027
 
7.2%
h20083
 
4.0%
E19397
 
3.9%
Other values (9)93421
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter407630
81.4%
Uppercase Letter37012
 
7.4%
Space Separator37012
 
7.4%
Other Punctuation19397
 
3.9%

Most frequent character per category

ValueCountFrequency (%)
e56409
13.8%
t55723
13.7%
o54926
13.5%
r54328
13.3%
m37012
9.1%
a36713
9.0%
i36027
8.8%
h20083
 
4.9%
n19397
 
4.8%
p19397
 
4.8%
Other values (3)17615
 
4.3%
ValueCountFrequency (%)
E19397
52.4%
P16630
44.9%
S686
 
1.9%
H299
 
0.8%
ValueCountFrequency (%)
37012
100.0%
ValueCountFrequency (%)
/19397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin444642
88.7%
Common56409
 
11.3%

Most frequent character per script

ValueCountFrequency (%)
e56409
12.7%
t55723
12.5%
o54926
12.4%
r54328
12.2%
m37012
8.3%
a36713
8.3%
i36027
8.1%
h20083
 
4.5%
E19397
 
4.4%
n19397
 
4.4%
Other values (7)54627
12.3%
ValueCountFrequency (%)
37012
65.6%
/19397
34.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII501051
100.0%

Most frequent character per block

ValueCountFrequency (%)
e56409
11.3%
t55723
11.1%
o54926
11.0%
r54328
10.8%
37012
 
7.4%
m37012
 
7.4%
a36713
 
7.3%
i36027
 
7.2%
h20083
 
4.0%
E19397
 
3.9%
Other values (9)93421
18.6%

accommodates
Real number (ℝ≥0)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7976332
Minimum0
Maximum16
Zeros13
Zeros (%)< 0.1%
Memory size289.3 KiB
2021-04-12T21:32:45.584152image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile6
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.845570338
Coefficient of variation (CV)0.6596898899
Kurtosis10.135629
Mean2.7976332
Median Absolute Deviation (MAD)1
Skewness2.471444523
Sum103546
Variance3.406129871
MonotocityNot monotonic
2021-04-12T21:32:45.693208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
216832
45.5%
16229
 
16.8%
45594
 
15.1%
33820
 
10.3%
61721
 
4.6%
51500
 
4.1%
8486
 
1.3%
7320
 
0.9%
10174
 
0.5%
1689
 
0.2%
Other values (7)247
 
0.7%
ValueCountFrequency (%)
013
 
< 0.1%
16229
 
16.8%
216832
45.5%
33820
 
10.3%
45594
 
15.1%
ValueCountFrequency (%)
1689
0.2%
1513
 
< 0.1%
1421
 
0.1%
1323
 
0.1%
1286
0.2%

bathrooms_text
Categorical

Distinct36
Distinct (%)0.1%
Missing102
Missing (%)0.3%
Memory size289.3 KiB
1 bath
19138 
1 shared bath
9420 
2 baths
2190 
1 private bath
2096 
1.5 baths
 
1057
Other values (31)
3009 

Length

Max length17
Median length6
Mean length8.962557572
Min length6

Characters and Unicode

Total characters330808
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1 bath
2nd row1 bath
3rd row1 bath
4th row1 shared bath
5th row1.5 baths
ValueCountFrequency (%)
1 bath19138
51.7%
1 shared bath9420
25.5%
2 baths2190
 
5.9%
1 private bath2096
 
5.7%
1.5 baths1057
 
2.9%
2 shared baths1055
 
2.9%
1.5 shared baths745
 
2.0%
2.5 baths305
 
0.8%
3 baths225
 
0.6%
0 shared baths127
 
0.3%
Other values (26)552
 
1.5%
(Missing)102
 
0.3%
2021-04-12T21:32:45.965084image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
130654
35.0%
bath30654
35.0%
shared11631
 
13.3%
baths6185
 
7.1%
23245
 
3.7%
private2113
 
2.4%
1.51802
 
2.1%
2.5400
 
0.5%
3322
 
0.4%
0164
 
0.2%
Other values (12)323
 
0.4%

Most occurring characters

ValueCountFrequency (%)
a50725
15.3%
50583
15.3%
h48576
14.7%
t39023
11.8%
b36910
11.2%
132457
9.8%
s17798
 
5.4%
r13744
 
4.2%
e13744
 
4.2%
d11631
 
3.5%
Other values (18)15617
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter238615
72.1%
Space Separator50583
 
15.3%
Decimal Number39154
 
11.8%
Other Punctuation2314
 
0.7%
Uppercase Letter71
 
< 0.1%
Dash Punctuation71
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
a50725
21.3%
h48576
20.4%
t39023
16.4%
b36910
15.5%
s17798
 
7.5%
r13744
 
5.8%
e13744
 
5.8%
d11631
 
4.9%
i2113
 
0.9%
v2113
 
0.9%
Other values (3)2238
 
0.9%
ValueCountFrequency (%)
132457
82.9%
23645
 
9.3%
52336
 
6.0%
3396
 
1.0%
0164
 
0.4%
4122
 
0.3%
619
 
< 0.1%
89
 
< 0.1%
76
 
< 0.1%
ValueCountFrequency (%)
H36
50.7%
S18
25.4%
P17
23.9%
ValueCountFrequency (%)
50583
100.0%
ValueCountFrequency (%)
.2314
100.0%
ValueCountFrequency (%)
-71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin238686
72.2%
Common92122
 
27.8%

Most frequent character per script

ValueCountFrequency (%)
a50725
21.3%
h48576
20.4%
t39023
16.3%
b36910
15.5%
s17798
 
7.5%
r13744
 
5.8%
e13744
 
5.8%
d11631
 
4.9%
i2113
 
0.9%
v2113
 
0.9%
Other values (6)2309
 
1.0%
ValueCountFrequency (%)
50583
54.9%
132457
35.2%
23645
 
4.0%
52336
 
2.5%
.2314
 
2.5%
3396
 
0.4%
0164
 
0.2%
4122
 
0.1%
-71
 
0.1%
619
 
< 0.1%
Other values (2)15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII330808
100.0%

Most frequent character per block

ValueCountFrequency (%)
a50725
15.3%
50583
15.3%
h48576
14.7%
t39023
11.8%
b36910
11.2%
132457
9.8%
s17798
 
5.4%
r13744
 
4.2%
e13744
 
4.2%
d11631
 
3.5%
Other values (18)15617
 
4.7%

bedrooms
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)< 0.1%
Missing3608
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean1.316399234
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:46.065081image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum21
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.72209385
Coefficient of variation (CV)0.5485371243
Kurtosis36.14433529
Mean1.316399234
Median Absolute Deviation (MAD)0
Skewness3.929790134
Sum43973
Variance0.5214195282
MonotocityNot monotonic
2021-04-12T21:32:46.166530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
126076
70.5%
25084
 
13.7%
31607
 
4.3%
4457
 
1.2%
5108
 
0.3%
628
 
0.1%
717
 
< 0.1%
816
 
< 0.1%
94
 
< 0.1%
103
 
< 0.1%
Other values (4)4
 
< 0.1%
(Missing)3608
 
9.7%
ValueCountFrequency (%)
126076
70.5%
25084
 
13.7%
31607
 
4.3%
4457
 
1.2%
5108
 
0.3%
ValueCountFrequency (%)
211
 
< 0.1%
141
 
< 0.1%
131
 
< 0.1%
111
 
< 0.1%
103
< 0.1%

beds
Real number (ℝ≥0)

MISSING
ZEROS

Distinct21
Distinct (%)0.1%
Missing490
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean1.533924758
Minimum0
Maximum42
Zeros1391
Zeros (%)3.8%
Memory size289.3 KiB
2021-04-12T21:32:46.278496image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum42
Range42
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.141557468
Coefficient of variation (CV)0.7442069515
Kurtosis65.96075852
Mean1.533924758
Median Absolute Deviation (MAD)0
Skewness4.437178241
Sum56022
Variance1.303153452
MonotocityNot monotonic
2021-04-12T21:32:46.381072image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
122771
61.5%
27689
 
20.8%
32698
 
7.3%
01391
 
3.8%
41160
 
3.1%
5389
 
1.1%
6201
 
0.5%
786
 
0.2%
854
 
0.1%
930
 
0.1%
Other values (11)53
 
0.1%
(Missing)490
 
1.3%
ValueCountFrequency (%)
01391
 
3.8%
122771
61.5%
27689
 
20.8%
32698
 
7.3%
41160
 
3.1%
ValueCountFrequency (%)
421
< 0.1%
241
< 0.1%
211
< 0.1%
181
< 0.1%
171
< 0.1%

amenities
Categorical

HIGH CARDINALITY

Distinct31671
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size289.3 KiB
["Long term stays allowed"]
 
138
["Smoke alarm", "Hangers", "Dedicated workspace", "Lock on bedroom door", "Wifi", "Heating", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]
 
50
["Essentials", "TV", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]
 
36
["Smoke alarm", "Essentials", "TV", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]
 
35
["Hair dryer", "Iron", "Hangers", "Essentials", "Washer", "TV", "Smoke alarm", "Dryer", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]
 
35
Other values (31666)
36718 

Length

Max length1865
Median length290
Mean length317.3961418
Min length2

Characters and Unicode

Total characters11747466
Distinct characters79
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29567 ?
Unique (%)79.9%

Sample

1st row["Refrigerator", "Air conditioning", "Baking sheet", "Free street parking", "Bathtub", "Kitchen", "Keypad", "Coffee maker", "Oven", "Iron", "Hangers", "Smoke alarm", "Dedicated workspace", "Fire extinguisher", "Hot water", "Long term stays allowed", "Extra pillows and blankets", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Heating", "Paid parking off premises", "Cooking basics", "Stove", "Luggage dropoff allowed", "Cleaning before checkout", "Carbon monoxide alarm", "Ethernet connection"]
2nd row["Refrigerator", "Microwave", "Shampoo", "High chair", "Pack \u2019n Play/travel crib", "Air conditioning", "Free street parking", "Bathtub", "Kitchen", "Coffee maker", "Oven", "Free parking on premises", "Iron", "Hangers", "Smoke alarm", "Dedicated workspace", "Fire extinguisher", "Hot water", "Children\u2019s books and toys", "Long term stays allowed", "Extra pillows and blankets", "Lockbox", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Cable TV", "Heating", "Cooking basics", "Stove", "Luggage dropoff allowed", "Baby safety gates", "Carbon monoxide alarm"]
3rd row["Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]
4th row["Extra pillows and blankets", "Hair dryer", "Bed linens", "Iron", "Essentials", "Hangers", "Smoke alarm", "TV", "Refrigerator", "Lock on bedroom door", "Shampoo", "Heating", "Wifi", "Microwave", "Paid parking off premises", "Luggage dropoff allowed", "Air conditioning", "Free street parking"]
5th row["Hair dryer", "Breakfast", "Smoke alarm", "Essentials", "Dedicated workspace", "Host greets you", "Wifi", "Shampoo", "Heating", "Fire extinguisher", "Paid parking off premises", "Elevator", "Free street parking", "Hot water", "Air conditioning", "Carbon monoxide alarm"]
ValueCountFrequency (%)
["Long term stays allowed"]138
 
0.4%
["Smoke alarm", "Hangers", "Dedicated workspace", "Lock on bedroom door", "Wifi", "Heating", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]50
 
0.1%
["Essentials", "TV", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]36
 
0.1%
["Smoke alarm", "Essentials", "TV", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]35
 
0.1%
["Hair dryer", "Iron", "Hangers", "Essentials", "Washer", "TV", "Smoke alarm", "Dryer", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]35
 
0.1%
["TV", "Wifi", "Cable TV", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]35
 
0.1%
["Smoke alarm", "Essentials", "TV", "Wifi", "Cable TV", "Heating", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]35
 
0.1%
["Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]32
 
0.1%
["Essentials", "Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]32
 
0.1%
["Hangers", "Dedicated workspace", "Wifi", "Lock on bedroom door", "Heating", "Long term stays allowed", "Kitchen"]31
 
0.1%
Other values (31661)36553
98.8%
2021-04-12T21:32:46.800640image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
alarm59322
 
4.3%
allowed41131
 
3.0%
dryer39218
 
2.9%
wifi36578
 
2.7%
heating34922
 
2.6%
stays34838
 
2.5%
long34838
 
2.5%
term34838
 
2.5%
tv34459
 
2.5%
essentials33864
 
2.5%
Other values (657)983156
71.9%

Most occurring characters

ValueCountFrequency (%)
"1514004
12.9%
1330177
 
11.3%
e880076
 
7.5%
a721291
 
6.1%
,720199
 
6.1%
r705925
 
6.0%
i659027
 
5.6%
o625760
 
5.3%
n540171
 
4.6%
t467025
 
4.0%
Other values (69)3583811
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7280319
62.0%
Other Punctuation2239514
 
19.1%
Space Separator1330177
 
11.3%
Uppercase Letter806456
 
6.9%
Open Punctuation37015
 
0.3%
Close Punctuation37015
 
0.3%
Decimal Number14742
 
0.1%
Dash Punctuation2184
 
< 0.1%
Currency Symbol41
 
< 0.1%
Math Symbol3
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
H115859
14.4%
S76366
 
9.5%
C70201
 
8.7%
D63178
 
7.8%
L56699
 
7.0%
W53571
 
6.6%
E53095
 
6.6%
F45033
 
5.6%
K35674
 
4.4%
T35206
 
4.4%
Other values (16)201574
25.0%
ValueCountFrequency (%)
e880076
12.1%
a721291
9.9%
r705925
9.7%
i659027
 
9.1%
o625760
 
8.6%
n540171
 
7.4%
t467025
 
6.4%
s453099
 
6.2%
l279565
 
3.8%
d279332
 
3.8%
Other values (16)1669048
22.9%
ValueCountFrequency (%)
04095
27.8%
23500
23.7%
13467
23.5%
92971
20.2%
3453
 
3.1%
4116
 
0.8%
595
 
0.6%
620
 
0.1%
814
 
0.1%
711
 
0.1%
ValueCountFrequency (%)
"1514004
67.6%
,720199
32.2%
\3718
 
0.2%
/1329
 
0.1%
:171
 
< 0.1%
&55
 
< 0.1%
.20
 
< 0.1%
'17
 
< 0.1%
%1
 
< 0.1%
ValueCountFrequency (%)
[37012
> 99.9%
(3
 
< 0.1%
ValueCountFrequency (%)
]37012
> 99.9%
)3
 
< 0.1%
ValueCountFrequency (%)
1330177
100.0%
ValueCountFrequency (%)
-2184
100.0%
ValueCountFrequency (%)
$41
100.0%
ValueCountFrequency (%)
+3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8086775
68.8%
Common3660691
31.2%

Most frequent character per script

ValueCountFrequency (%)
e880076
 
10.9%
a721291
 
8.9%
r705925
 
8.7%
i659027
 
8.1%
o625760
 
7.7%
n540171
 
6.7%
t467025
 
5.8%
s453099
 
5.6%
l279565
 
3.5%
d279332
 
3.5%
Other values (42)2475504
30.6%
ValueCountFrequency (%)
"1514004
41.4%
1330177
36.3%
,720199
19.7%
[37012
 
1.0%
]37012
 
1.0%
04095
 
0.1%
\3718
 
0.1%
23500
 
0.1%
13467
 
0.1%
92971
 
0.1%
Other values (17)4536
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII11747466
100.0%

Most frequent character per block

ValueCountFrequency (%)
"1514004
12.9%
1330177
 
11.3%
e880076
 
7.5%
a721291
 
6.1%
,720199
 
6.1%
r705925
 
6.0%
i659027
 
5.6%
o625760
 
5.3%
n540171
 
4.6%
t467025
 
4.0%
Other values (69)3583811
30.5%

price
Real number (ℝ≥0)

SKEWED

Distinct733
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142.8422404
Minimum0
Maximum10000
Zeros28
Zeros (%)0.1%
Memory size289.3 KiB
2021-04-12T21:32:46.946595image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35
Q160
median99
Q3151
95-th percentile349
Maximum10000
Range10000
Interquartile range (IQR)91

Descriptive statistics

Standard deviation275.7409867
Coefficient of variation (CV)1.93038828
Kurtosis651.7718796
Mean142.8422404
Median Absolute Deviation (MAD)44
Skewness21.2915869
Sum5286877
Variance76033.09173
MonotocityNot monotonic
2021-04-12T21:32:47.092598image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001357
 
3.7%
1501289
 
3.5%
501181
 
3.2%
60974
 
2.6%
75925
 
2.5%
80913
 
2.5%
70860
 
2.3%
65790
 
2.1%
120779
 
2.1%
200756
 
2.0%
Other values (723)27188
73.5%
ValueCountFrequency (%)
028
0.1%
106
 
< 0.1%
141
 
< 0.1%
154
 
< 0.1%
163
 
< 0.1%
ValueCountFrequency (%)
100006
< 0.1%
99995
< 0.1%
99901
 
< 0.1%
90001
 
< 0.1%
73141
 
< 0.1%

minimum_nights
Real number (ℝ≥0)

Distinct125
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.32367881
Minimum1
Maximum1250
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:47.230688image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median30
Q330
95-th percentile30
Maximum1250
Range1249
Interquartile range (IQR)26

Descriptive statistics

Standard deviation26.44125451
Coefficient of variation (CV)1.133665694
Kurtosis425.2302795
Mean23.32367881
Median Absolute Deviation (MAD)0
Skewness14.32176548
Sum863256
Variance699.1399402
MonotocityNot monotonic
2021-04-12T21:32:47.375065image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3023557
63.6%
13719
 
10.0%
22874
 
7.8%
32192
 
5.9%
5864
 
2.3%
4825
 
2.2%
7662
 
1.8%
31374
 
1.0%
14275
 
0.7%
6211
 
0.6%
Other values (115)1459
 
3.9%
ValueCountFrequency (%)
13719
10.0%
22874
7.8%
32192
5.9%
4825
 
2.2%
5864
 
2.3%
ValueCountFrequency (%)
12501
 
< 0.1%
11241
 
< 0.1%
10002
 
< 0.1%
9991
 
< 0.1%
5005
< 0.1%

maximum_nights
Real number (ℝ≥0)

SKEWED

Distinct278
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59799.23998
Minimum1
Maximum2147483647
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:47.526068image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q190
median1125
Q31125
95-th percentile1125
Maximum2147483647
Range2147483646
Interquartile range (IQR)1035

Descriptive statistics

Standard deviation11163384.71
Coefficient of variation (CV)186.6810468
Kurtosis36999.1628
Mean59799.23998
Median Absolute Deviation (MAD)0
Skewness192.3352933
Sum2213289470
Variance1.246211583 × 1014
MonotocityNot monotonic
2021-04-12T21:32:47.666097image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112520729
56.0%
302805
 
7.6%
3652434
 
6.6%
901506
 
4.1%
601209
 
3.3%
28773
 
2.1%
180729
 
2.0%
31596
 
1.6%
120463
 
1.3%
14385
 
1.0%
Other values (268)5383
 
14.5%
ValueCountFrequency (%)
153
0.1%
238
0.1%
373
0.2%
465
0.2%
589
0.2%
ValueCountFrequency (%)
21474836471
 
< 0.1%
200000002
< 0.1%
100002
< 0.1%
99993
< 0.1%
60001
 
< 0.1%

availability_30
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.75308008
Minimum0
Maximum30
Zeros19305
Zeros (%)52.2%
Memory size289.3 KiB
2021-04-12T21:32:47.792063image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q328
95-th percentile30
Maximum30
Range30
Interquartile range (IQR)28

Descriptive statistics

Standard deviation13.0881565
Coefficient of variation (CV)1.217154192
Kurtosis-1.554475767
Mean10.75308008
Median Absolute Deviation (MAD)0
Skewness0.5564619038
Sum397993
Variance171.2998406
MonotocityNot monotonic
2021-04-12T21:32:47.907098image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
019305
52.2%
305651
 
15.3%
292755
 
7.4%
281243
 
3.4%
1749
 
2.0%
27712
 
1.9%
23672
 
1.8%
6657
 
1.8%
7648
 
1.8%
24341
 
0.9%
Other values (21)4279
 
11.6%
ValueCountFrequency (%)
019305
52.2%
1749
 
2.0%
2217
 
0.6%
3172
 
0.5%
4183
 
0.5%
ValueCountFrequency (%)
305651
15.3%
292755
7.4%
281243
 
3.4%
27712
 
1.9%
26260
 
0.7%

availability_60
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct61
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.86542203
Minimum0
Maximum60
Zeros17604
Zeros (%)47.6%
Memory size289.3 KiB
2021-04-12T21:32:48.039087image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q357
95-th percentile60
Maximum60
Range60
Interquartile range (IQR)57

Descriptive statistics

Standard deviation26.54952182
Coefficient of variation (CV)1.112468147
Kurtosis-1.713194176
Mean23.86542203
Median Absolute Deviation (MAD)4
Skewness0.3685037842
Sum883307
Variance704.8771086
MonotocityNot monotonic
2021-04-12T21:32:48.176911image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
017604
47.6%
605442
 
14.7%
592634
 
7.1%
581171
 
3.2%
57656
 
1.8%
1616
 
1.7%
53574
 
1.6%
37555
 
1.5%
36530
 
1.4%
5418
 
1.1%
Other values (51)6812
 
18.4%
ValueCountFrequency (%)
017604
47.6%
1616
 
1.7%
2117
 
0.3%
394
 
0.3%
4113
 
0.3%
ValueCountFrequency (%)
605442
14.7%
592634
7.1%
581171
 
3.2%
57656
 
1.8%
56237
 
0.6%

availability_90
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct91
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.61555712
Minimum0
Maximum90
Zeros16770
Zeros (%)45.3%
Memory size289.3 KiB
2021-04-12T21:32:48.320959image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q387
95-th percentile90
Maximum90
Range90
Interquartile range (IQR)87

Descriptive statistics

Standard deviation39.9055824
Coefficient of variation (CV)1.060879739
Kurtosis-1.759427918
Mean37.61555712
Median Absolute Deviation (MAD)15
Skewness0.2810817152
Sum1392227
Variance1592.455507
MonotocityNot monotonic
2021-04-12T21:32:48.453602image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
016770
45.3%
905108
 
13.8%
892741
 
7.4%
881190
 
3.2%
87662
 
1.8%
83582
 
1.6%
1557
 
1.5%
66497
 
1.3%
67481
 
1.3%
35380
 
1.0%
Other values (81)8044
21.7%
ValueCountFrequency (%)
016770
45.3%
1557
 
1.5%
277
 
0.2%
371
 
0.2%
4101
 
0.3%
ValueCountFrequency (%)
905108
13.8%
892741
7.4%
881190
 
3.2%
87662
 
1.8%
86232
 
0.6%

availability_365
Real number (ℝ≥0)

ZEROS

Distinct366
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130.2828002
Minimum0
Maximum365
Zeros15121
Zeros (%)40.9%
Memory size289.3 KiB
2021-04-12T21:32:48.613142image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median66
Q3292
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)292

Descriptive statistics

Standard deviation146.6352721
Coefficient of variation (CV)1.125515202
Kurtosis-1.32306729
Mean130.2828002
Median Absolute Deviation (MAD)66
Skewness0.6028210157
Sum4822027
Variance21501.90303
MonotocityNot monotonic
2021-04-12T21:32:48.761709image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
015121
40.9%
3653176
 
8.6%
3641327
 
3.6%
179795
 
2.1%
89762
 
2.1%
90567
 
1.5%
180554
 
1.5%
363521
 
1.4%
1469
 
1.3%
88369
 
1.0%
Other values (356)13351
36.1%
ValueCountFrequency (%)
015121
40.9%
1469
 
1.3%
262
 
0.2%
355
 
0.1%
484
 
0.2%
ValueCountFrequency (%)
3653176
8.6%
3641327
3.6%
363521
 
1.4%
362258
 
0.7%
361107
 
0.3%

number_of_reviews
Real number (ℝ≥0)

ZEROS

Distinct388
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.90411218
Minimum0
Maximum753
Zeros9523
Zeros (%)25.7%
Memory size289.3 KiB
2021-04-12T21:32:48.911766image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q320
95-th percentile119
Maximum753
Range753
Interquartile range (IQR)20

Descriptive statistics

Standard deviation47.86471966
Coefficient of variation (CV)2.089787165
Kurtosis20.93086257
Mean22.90411218
Median Absolute Deviation (MAD)4
Skewness3.869551903
Sum847727
Variance2291.031388
MonotocityNot monotonic
2021-04-12T21:32:49.046217image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09523
25.7%
14116
 
11.1%
22572
 
6.9%
31844
 
5.0%
41426
 
3.9%
51155
 
3.1%
6942
 
2.5%
7849
 
2.3%
8727
 
2.0%
9642
 
1.7%
Other values (378)13216
35.7%
ValueCountFrequency (%)
09523
25.7%
14116
11.1%
22572
 
6.9%
31844
 
5.0%
41426
 
3.9%
ValueCountFrequency (%)
7531
< 0.1%
6401
< 0.1%
5981
< 0.1%
5911
< 0.1%
5641
< 0.1%

number_of_reviews_ltm
Real number (ℝ≥0)

ZEROS

Distinct122
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.75264779
Minimum0
Maximum514
Zeros23720
Zeros (%)64.1%
Memory size289.3 KiB
2021-04-12T21:32:49.197063image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile14
Maximum514
Range514
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.58204757
Coefficient of variation (CV)3.481029286
Kurtosis624.5637378
Mean2.75264779
Median Absolute Deviation (MAD)0
Skewness17.00727231
Sum101881
Variance91.81563564
MonotocityNot monotonic
2021-04-12T21:32:49.343881image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023720
64.1%
13573
 
9.7%
22005
 
5.4%
31340
 
3.6%
41020
 
2.8%
5733
 
2.0%
6590
 
1.6%
7478
 
1.3%
8394
 
1.1%
9317
 
0.9%
Other values (112)2842
 
7.7%
ValueCountFrequency (%)
023720
64.1%
13573
 
9.7%
22005
 
5.4%
31340
 
3.6%
41020
 
2.8%
ValueCountFrequency (%)
5141
< 0.1%
4791
< 0.1%
3951
< 0.1%
3911
< 0.1%
3391
< 0.1%

first_review
Date

MISSING

Distinct3274
Distinct (%)11.9%
Missing9523
Missing (%)25.7%
Memory size289.3 KiB
Minimum2009-04-23 00:00:00
Maximum2021-02-05 00:00:00
2021-04-12T21:32:49.485027image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:49.635038image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

last_review
Date

MISSING

Distinct2226
Distinct (%)8.1%
Missing9523
Missing (%)25.7%
Memory size289.3 KiB
Minimum2010-12-21 00:00:00
Maximum2021-02-05 00:00:00
2021-04-12T21:32:49.793077image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:49.933035image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

review_scores_rating
Real number (ℝ≥0)

MISSING

Distinct53
Distinct (%)0.2%
Missing10235
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean93.76718826
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:51.120123image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile80
Q192
median97
Q3100
95-th percentile100
Maximum100
Range80
Interquartile range (IQR)8

Descriptive statistics

Standard deviation9.594490711
Coefficient of variation (CV)0.1023224743
Kurtosis21.24862842
Mean93.76718826
Median Absolute Deviation (MAD)3
Skewness-3.840689419
Sum2510804
Variance92.054252
MonotocityNot monotonic
2021-04-12T21:32:51.245334image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1008325
22.5%
982051
 
5.5%
961869
 
5.0%
971797
 
4.9%
951594
 
4.3%
931520
 
4.1%
901299
 
3.5%
991246
 
3.4%
941153
 
3.1%
801149
 
3.1%
Other values (43)4774
12.9%
(Missing)10235
27.7%
ValueCountFrequency (%)
20133
0.4%
305
 
< 0.1%
351
 
< 0.1%
4087
0.2%
451
 
< 0.1%
ValueCountFrequency (%)
1008325
22.5%
991246
 
3.4%
982051
 
5.5%
971797
 
4.9%
961869
 
5.0%

review_scores_accuracy
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing10259
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean9.586551041
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:51.354337image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q19
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9388813799
Coefficient of variation (CV)0.09793734742
Kurtosis24.71035357
Mean9.586551041
Median Absolute Deviation (MAD)0
Skewness-4.204932714
Sum256469
Variance0.8814982455
MonotocityNot monotonic
2021-04-12T21:32:51.441812image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1019559
52.8%
95272
 
14.2%
81170
 
3.2%
6262
 
0.7%
7255
 
0.7%
2127
 
0.3%
472
 
0.2%
532
 
0.1%
34
 
< 0.1%
(Missing)10259
27.7%
ValueCountFrequency (%)
2127
0.3%
34
 
< 0.1%
472
 
0.2%
532
 
0.1%
6262
0.7%
ValueCountFrequency (%)
1019559
52.8%
95272
 
14.2%
81170
 
3.2%
7255
 
0.7%
6262
 
0.7%

review_scores_cleanliness
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing10248
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean9.268009266
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:51.536811image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7
Q19
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.146265591
Coefficient of variation (CV)0.1236798063
Kurtosis11.86308107
Mean9.268009266
Median Absolute Deviation (MAD)0
Skewness-2.844901053
Sum248049
Variance1.313924804
MonotocityNot monotonic
2021-04-12T21:32:51.628393image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1014705
39.7%
97897
21.3%
82670
 
7.2%
7631
 
1.7%
6484
 
1.3%
2171
 
0.5%
4113
 
0.3%
586
 
0.2%
37
 
< 0.1%
(Missing)10248
27.7%
ValueCountFrequency (%)
2171
 
0.5%
37
 
< 0.1%
4113
 
0.3%
586
 
0.2%
6484
1.3%
ValueCountFrequency (%)
1014705
39.7%
97897
21.3%
82670
 
7.2%
7631
 
1.7%
6484
 
1.3%

review_scores_checkin
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing10271
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean9.721139823
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:51.726403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile9
Q110
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8239482918
Coefficient of variation (CV)0.08475840352
Kurtosis38.31977437
Mean9.721139823
Median Absolute Deviation (MAD)0
Skewness-5.338310486
Sum259953
Variance0.6788907875
MonotocityNot monotonic
2021-04-12T21:32:51.819402image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1022007
59.5%
93473
 
9.4%
8726
 
2.0%
6186
 
0.5%
7169
 
0.5%
2111
 
0.3%
446
 
0.1%
522
 
0.1%
31
 
< 0.1%
(Missing)10271
27.8%
ValueCountFrequency (%)
2111
0.3%
31
 
< 0.1%
446
 
0.1%
522
 
0.1%
6186
0.5%
ValueCountFrequency (%)
1022007
59.5%
93473
 
9.4%
8726
 
2.0%
7169
 
0.5%
6186
 
0.5%

review_scores_communication
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing10257
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean9.712801346
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:51.915401image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q110
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.859563248
Coefficient of variation (CV)0.08849797473
Kurtosis36.77814331
Mean9.712801346
Median Absolute Deviation (MAD)0
Skewness-5.294269403
Sum259866
Variance0.7388489773
MonotocityNot monotonic
2021-04-12T21:32:52.005471image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1022059
59.6%
93337
 
9.0%
8780
 
2.1%
6199
 
0.5%
7176
 
0.5%
2128
 
0.3%
451
 
0.1%
521
 
0.1%
34
 
< 0.1%
(Missing)10257
27.7%
ValueCountFrequency (%)
2128
0.3%
34
 
< 0.1%
451
 
0.1%
521
 
0.1%
6199
0.5%
ValueCountFrequency (%)
1022059
59.6%
93337
 
9.0%
8780
 
2.1%
7176
 
0.5%
6199
 
0.5%

review_scores_location
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing10272
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean9.599588631
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:52.100479image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q19
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7947666129
Coefficient of variation (CV)0.08279173654
Kurtosis24.76935634
Mean9.599588631
Median Absolute Deviation (MAD)0
Skewness-3.829538466
Sum256693
Variance0.6316539689
MonotocityNot monotonic
2021-04-12T21:32:52.194040image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1018819
50.8%
96220
 
16.8%
81245
 
3.4%
6200
 
0.5%
7151
 
0.4%
264
 
0.2%
427
 
0.1%
514
 
< 0.1%
(Missing)10272
27.8%
ValueCountFrequency (%)
264
 
0.2%
427
 
0.1%
514
 
< 0.1%
6200
0.5%
7151
0.4%
ValueCountFrequency (%)
1018819
50.8%
96220
 
16.8%
81245
 
3.4%
7151
 
0.4%
6200
 
0.5%

review_scores_value
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing10272
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean9.367539267
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:52.295049image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q19
median10
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.014200827
Coefficient of variation (CV)0.1082675821
Kurtosis16.32497789
Mean9.367539267
Median Absolute Deviation (MAD)0
Skewness-3.244901803
Sum250488
Variance1.028603317
MonotocityNot monotonic
2021-04-12T21:32:52.397050image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1015096
40.8%
98723
23.6%
81959
 
5.3%
7343
 
0.9%
6340
 
0.9%
2129
 
0.3%
492
 
0.2%
554
 
0.1%
34
 
< 0.1%
(Missing)10272
27.8%
ValueCountFrequency (%)
2129
 
0.3%
34
 
< 0.1%
492
 
0.2%
554
 
0.1%
6340
0.9%
ValueCountFrequency (%)
1015096
40.8%
98723
23.6%
81959
 
5.3%
7343
 
0.9%
6340
 
0.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.3 KiB
False
25972 
True
11040 
ValueCountFrequency (%)
False25972
70.2%
True11040
29.8%
2021-04-12T21:32:52.475092image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

reviews_per_month
Real number (ℝ≥0)

MISSING

Distinct752
Distinct (%)2.7%
Missing9523
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean0.8671970606
Minimum0.01
Maximum40.31
Zeros0
Zeros (%)0.0%
Memory size289.3 KiB
2021-04-12T21:32:52.573570image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.03
Q10.11
median0.36
Q31.12
95-th percentile3.236
Maximum40.31
Range40.3
Interquartile range (IQR)1.01

Descriptive statistics

Standard deviation1.320502533
Coefficient of variation (CV)1.522724872
Kurtosis103.3284888
Mean0.8671970606
Median Absolute Deviation (MAD)0.31
Skewness6.047037686
Sum23838.38
Variance1.74372694
MonotocityNot monotonic
2021-04-12T21:32:52.719599image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.021091
 
2.9%
0.03892
 
2.4%
0.07791
 
2.1%
0.05762
 
2.1%
0.04684
 
1.8%
0.06634
 
1.7%
0.08562
 
1.5%
0.09539
 
1.5%
0.11472
 
1.3%
0.1438
 
1.2%
Other values (742)20624
55.7%
(Missing)9523
25.7%
ValueCountFrequency (%)
0.01268
 
0.7%
0.021091
2.9%
0.03892
2.4%
0.04684
1.8%
0.05762
2.1%
ValueCountFrequency (%)
40.311
< 0.1%
39.021
< 0.1%
34.331
< 0.1%
30.821
< 0.1%
27.061
< 0.1%

Interactions

2021-04-12T21:31:11.315620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:31:11.446103image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:31:11.583104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-04-12T21:32:33.743279image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:33.879856image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.021724image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.157998image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.298034image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.434994image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.581564image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-04-12T21:32:34.723523image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2021-04-12T21:32:52.891601image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-04-12T21:32:53.234968image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-04-12T21:32:53.565056image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-04-12T21:32:53.912023image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-04-12T21:32:54.272753image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-04-12T21:32:35.324543image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-04-12T21:32:37.249707image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-04-12T21:32:38.629397image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-04-12T21:32:39.296203image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

last_scrapednamedescriptionneighborhood_overviewhost_sincehost_abouthost_response_timehost_response_ratehost_acceptance_ratehost_is_superhosthost_total_listings_counthost_verificationshost_has_profile_pichost_identity_verifiedneighbourhood_cleansedneighbourhood_group_cleansedlatitudelongitudeproperty_typeroom_typeaccommodatesbathrooms_textbedroomsbedsamenitiespriceminimum_nightsmaximum_nightsavailability_30availability_60availability_90availability_365number_of_reviewsnumber_of_reviews_ltmfirst_reviewlast_reviewreview_scores_ratingreview_scores_accuracyreview_scores_cleanlinessreview_scores_checkinreview_scores_communicationreview_scores_locationreview_scores_valueinstant_bookablereviews_per_month
02021-02-05Skylit Midtown CastleBeautiful, spacious skylit studio in the heart of Midtown, Manhattan. <br /><br />STUNNING SKYLIT STUDIO / 1 BED + SINGLE / FULL BATH / FULL KITCHEN / FIREPLACE / CENTRALLY LOCATED / WiFi + APPLE TV / SHEETS + TOWELS<br /><br /><b>The space</b><br />- Spacious (500+ft²), immaculate and nicely furnished & designed studio.<br />- Tuck yourself into the ultra comfortable bed under the skylight. Fall in love with a myriad of bright lights in the city night sky. <br />- Single-sized bed/convertible floor mattress with luxury bedding (available upon request).<br />- Gorgeous pyramid skylight with amazing diffused natural light, stunning architectural details, soaring high vaulted ceilings, exposed brick, wood burning fireplace, floor seating area with natural zafu cushions, modern style mixed with eclectic art & antique treasures, large full bath, newly renovated kitchen, air conditioning/heat, high speed WiFi Internet, and Apple TV.<br />- Centrally located in the heart of Midtown ManhattanCentrally located in the heart of Manhattan just a few blocks from all subway connections in the very desirable Midtown location a few minutes walk to Times Square, the Theater District, Bryant Park and Herald Square.2008-09-09A New Yorker since 2000! My passion is creating beautiful, unique spaces where unforgettable memories are made. It's my pleasure to host people from around the world and meet new faces. Welcome travelers! \r\n\r\nI am a Sound Therapy Practitioner and Kundalini Yoga & Meditation teacher. I work with energy and sound for relaxation and healing, using Symphonic gong, singing bowls, tuning forks, drums, voice and other instruments.within a few hours93.026.0f6.0['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'selfie', 'government_id', 'identity_manual', 'work_email']ttMidtownManhattan40.75362-73.98377Entire apartmentEntire home/apt21 bathNaN1.0["Refrigerator", "Air conditioning", "Baking sheet", "Free street parking", "Bathtub", "Kitchen", "Keypad", "Coffee maker", "Oven", "Iron", "Hangers", "Smoke alarm", "Dedicated workspace", "Fire extinguisher", "Hot water", "Long term stays allowed", "Extra pillows and blankets", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Heating", "Paid parking off premises", "Cooking basics", "Stove", "Luggage dropoff allowed", "Cleaning before checkout", "Carbon monoxide alarm", "Ethernet connection"]100.03011253060903654802009-11-212019-11-0494.09.09.010.010.010.09.0f0.35
12021-02-05Whole flr w/private bdrm, bath & kitchen(pls read)Enjoy 500 s.f. top floor in 1899 brownstone, w/ wood & ceramic flooring throughout, roomy bdrm, & upgraded kitchen & bathroom.  This space is unique but one of the few legal AirBnbs with a totally private bedroom, private full bathroom and private eat-in kitchen, SO PLEASE READ "THE SPACE" CAREFULLY.  It's sunny & loaded with everything you need! Your floor, and the common staircase/hallway/entryway are cleaned/sanitized per Airbnb's Enhanced Cleaning Protocol.<br /><br /><b>The space</b><br />We host on the entire top floor of our double-duplex brownstone in Clinton Hill on Gates near Classon Avenue - (7 blocks to C train, 5 blocks to G train, minutes to downtown Brooklyn & lower Manhattan).  It is not an apartment in the traditional sense, it is more of an efficiency set-up and is TOTALLY LEGAL with all short-term rental laws. The top floor for our guests consists of a sizable bedroom, full bath and eat-in kitchen for your exclusive use - you get the amenities of a private apartmentJust the right mix of urban center and local neighborhood; close to all but enough quiet for a calming walk. 15 to 45 minutes to most parts of Manhattan; 10 to 30 minutes to most Brooklyn points of interest; 45 minutes to 60 minutes to historic Coney Island.2008-12-07Laid-back Native New Yorker (formerly bi-coastal) and AirBnb host of over 6 years and over 400 stays! Besides being a long-time and attentive AirBnb host, I am an actor, attorney, professor and group fitness instructor.within a few hours98.093.0f1.0['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'government_id']ttClinton HillBrooklyn40.68514-73.95976Entire guest suiteEntire home/apt31 bath1.03.0["Refrigerator", "Microwave", "Shampoo", "High chair", "Pack \u2019n Play/travel crib", "Air conditioning", "Free street parking", "Bathtub", "Kitchen", "Coffee maker", "Oven", "Free parking on premises", "Iron", "Hangers", "Smoke alarm", "Dedicated workspace", "Fire extinguisher", "Hot water", "Children\u2019s books and toys", "Long term stays allowed", "Extra pillows and blankets", "Lockbox", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Cable TV", "Heating", "Cooking basics", "Stove", "Luggage dropoff allowed", "Baby safety gates", "Carbon monoxide alarm"]73.0173062755249386802014-09-302021-01-2790.010.09.09.010.010.010.0f4.99
22021-02-05BlissArtsSpace!<b>The space</b><br />HELLO EVERYONE AND THANKS FOR VISITING BLISS ART SPACE! <br /><br />Thank you all for your support. I've traveled a lot in the last year few years, to the U.K. Germany, Italy and France! Loved Paris, Berlin and Calabria! Highly recommend all these places. <br /><br /><br />One room available for rent in a 2 bedroom apt in Bklyn. We share a common space with kitchen. I am an artist(painter, filmmaker) and curator who is working in the film industry while I'm building my art event production businesses.<br /><br />Price above is nightly for one person. Monthly rates available. Price is $900 per month for one person. Utilities not included, they are about 50 bucks, payable when the bill arrives mid month.<br /> <br />Couples rates are slightly more for monthly and 90$ per night short term. If you are a couple please Iet me know and I’ll give you the monthly rate for that. Room rental is on a temporary basis, perfect from 2- 6 months - no long term requests please!NaN2009-02-03I am an artist(painter, filmmaker) and curator who is working in the film industry while I'm building my business.\r\n\r\nI am extremely easy going and would like that you are the laid back\r\nand enjoy life kind of person. I also ask that you are open, honest\r\nand easy to communicate with as this is how I like to live my life.And of course creative people are very welcome!\r\nNaNNaNNaNf1.0['email', 'phone', 'facebook', 'reviews', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttBedford-StuyvesantBrooklyn40.68688-73.95596Private room in apartmentPrivate room2NaN1.01.0["Wifi", "Heating", "Air conditioning", "Long term stays allowed", "Kitchen"]60.0307303060903655002009-05-282019-12-0290.08.08.010.010.09.09.0f0.35
32021-02-05Large Furnished Room Near B'wayPlease don’t expect the luxury here just a basic room in the center of Manhattan.<br /><br /><b>The space</b><br />You will use one large, furnished, private room of a two-bedroom apartment and share a bathroom with the host. <br /><br />The apartment is located a few blocks away from Central Park between 8th and 9th Avenue.<br />The closest subway station is Columbus Circle 59th Street. Great restaurants, Broadway and all transportation are easily accessible. <br /><br />The cost of the room is $79 per night. Weekly rate is available.<br />There is a $12.00 fee per second guest. <br /><br />The apartment also features hardwood floors and a second-floor walk-up. <br />There is a full-sized bed,TV, microwave, and a small refrigerator as well as other appliances. <br />Wired internet, WIFI, TV, electric heat, bed sheets and towels are included. <br /><br />A kitchen is not available in the living room. Please ask the host if you need.<br /><br />Basic check in/out time is 10 am. I amTheater district, many restaurants around here.2009-03-03I used to work for a financial industry but now I work at a Japanese food market as an assistant manager.within a day100.0100.0f1.0['email', 'phone', 'facebook', 'reviews']tfMidtownManhattan40.76468-73.98315Private room in apartmentPrivate room21 bath1.01.0["Extra pillows and blankets", "Hair dryer", "Bed linens", "Iron", "Essentials", "Hangers", "Smoke alarm", "TV", "Refrigerator", "Lock on bedroom door", "Shampoo", "Heating", "Wifi", "Microwave", "Paid parking off premises", "Luggage dropoff allowed", "Air conditioning", "Free street parking"]79.0214295986343474102009-05-062020-09-2584.09.08.09.09.010.09.0f3.31
42021-02-06Cozy Clean Guest Room - Family AptOur best guests are seeking a safe, clean, spare room in a family apartment. They are comfortable being independent, accommodating of family noise (quiet hours 11pm-7am), and aren't afraid of a friendly two year old golden lab (dog). Our guests aren't put off by an old bathroom that while perfectly clean, has some peeling paint. In short, our guests want to feel like they are staying at their sister's apartment while visiting the city! (only their sister changed the sheets and cleaned).<br /><br /><b>The space</b><br />Stay in my family's little guest room and enjoy privacy, a warm welcome, and security. <br /><br />Your guest room is comfortable and clean. It is small but well outfitted, has a single bed and a fabulous mattress which is firm and yet pillowy on top, all at the same time. The bathroom is shared and immediately across the hall. ("Shared" in the sense it isn't "en suite." The family will use our second bath while you are staying with us). The bathroom is fully supplOur neighborhood is full of restaurants and cafes. There is plenty to do.2009-02-05Welcome to family life with my oldest two away at college all the way down to a seventh grader. You may see everything from lively dinner conversation to a nearly empty apartment with everyone out enjoying the city. I'm friendly, leave tea and coffee always available and responsive to a guest's needs. My family has enjoyed everything from the guest who tends towards the private as well as the ones who dive in with the science experiment! \r\nHosting through Airbnb has created a wonderful opportunity to meet people from all over the world, plot their addresses, and learn about other places. I began hosting through Airbnb four years ago as a work-from-home job. I continue because the whole family entirely grooves on the notion we get to meet people from all over the world and help them visit our city.NaNNaNNaNf1.0['email', 'phone', 'facebook', 'google', 'reviews', 'jumio', 'government_id']ttUpper West SideManhattan40.80178-73.96723Private room in apartmentPrivate room11 shared bath1.01.0["Hair dryer", "Breakfast", "Smoke alarm", "Essentials", "Dedicated workspace", "Host greets you", "Wifi", "Shampoo", "Heating", "Fire extinguisher", "Paid parking off premises", "Elevator", "Free street parking", "Hot water", "Air conditioning", "Carbon monoxide alarm"]75.0214000011802009-09-072017-07-2198.010.010.010.010.010.010.0f0.85
52021-02-05Lovely Room 1, Garden, Best Area, Legal rentalDiscounted now! Beautiful house, gorgeous garden, patio, cozy room, and helpful host! Super safe and quiet in beautiful, vibrant Park Slope! <br />Please read, then WRITE to me about your trip, and needs. Please do NOT request reservation until I reply "yes ". I want to be sure it's right for you!<br />Close to great restaurants, culture, Prospect Park. <br />3 minutes walk to 3 subway lines, 20 mins to Manhattan.<br />LEGAL rental -- per NY laws. <br />Six gyms nearby.<br /><br /><b>The space</b><br />Welcome to an historic, stunning 4-story Brooklyn house, in super safe, quiet and friendly Park Slope. 140 year old house filled with light, color, artwork. Large beautiful garden and patio. Legal rental. <br />Three excellent SUBWAY LINES (R, F, G) 2 minutes walk, 20 mins to Manhattan. <br />Please write to me with your details; Wait til I reply "yes" before requesting room.<br />Discounts available for longer stay.<br />Historic house with charming details, not "moNeighborhood is amazing!<br />Best subways to Manhattan, Williamsburg, Lower East Side (20 mins);<br />* Excellent affordable restaurants; Supermarket on corner.<br />* Close to Barclay's Center, Bell House, other good music clubs, cultural events;<br />* Near Prospect Park (free events, concerts) & Botanical Gardens <br />* Museum / Brooklyn Academy of Music <br />* Steps from NY Marathon route<br />* Flea Markets & bargain shopping<br />* YMCA, 5 gyms nearby; Street parking.2009-03-10Hello, \r\nI will be welcoming and helpful, while respecting your privacy. I know a lot about NY & Brooklyn and love my neighborhood. I'm especially interested in arts and music. \r\nI speak and understand several languages. I work at home a lot, on my main floor, and do prefer guests who are busy themselves, and casual, low-key, trusting and flexible people. \r\n It's an old house with quirks, (not a hotel!) in a fantastic and quiet location.\r\nIncluded: Laundry, excellent coffee & breakfast foods, nice linens, big garden & BBQ, fans, air conditioners. \r\nSome use of kitchen can be worked out.\r\nwithin an hour100.0100.0t3.0['email', 'phone', 'facebook', 'reviews', 'jumio', 'offline_government_id', 'government_id']ttSouth SlopeBrooklyn40.66829-73.98779Private room in townhousePrivate room21.5 baths1.00.0["Shampoo", "Air conditioning", "Free street parking", "Coffee maker", "Iron", "Hangers", "Smoke alarm", "Washer", "Dedicated workspace", "Dryer", "Fire extinguisher", "Hot water", "Long term stays allowed", "Lockbox", "Hair dryer", "Essentials", "Wifi", "Heating", "Patio or balcony", "First aid kit", "Luggage dropoff allowed", "Beach essentials", "Garden or backyard", "Carbon monoxide alarm"]83.049030609036518252009-04-232020-10-1794.010.010.010.010.010.010.0f1.27
62021-02-05Only 2 stops to Manhattan studioComfortable studio apartment with super comfortable king size bed and full kitchen and bathroom located in FABULOUS Williamsburg, Brooklyn.<br /><br /><b>The space</b><br />Our comfortable 500 sq foot (46 sq m) studio apartment with full kitchen and bath is for short term rental. The apartment is private and is in a two family house. The house is located in FABULOUS Williamsburg, Brooklyn within 10 minute travel from Manhattan. The studio is a perfect place to stay for budget minded visitors of New York City!<br /><br />IN THE APARTMENT:<br /><br />Comfortable luxury king size bed, soft flannel bed linens, pillows, comforters, a couch with queen size pullout bed, air conditioning, hangers, iron & ironing board, alarm clock, radio, TV(No Cable/Satellite), DVD/VCR player, wireless internet access for guest's laptops, dining table, room divider/screen<br /><br />IN THE BATHROOM: <br /><br />Fluffy bath towels, hand towels, bath mat, wash cloths, toilet paper (initial supply), plunger/toiNaN2009-05-06We love to travel. When we travel we like to stay in a comfortable place that is clean, neat and sweet smelling, for a reasonable price. That's what we rent to you. We love city life but we also love outdoor adventures. We like keep up with all that's new and exciting around New York and we're happy to tell you where to find it. Want to hear the new young musicians that people are excited about or the promising new artists - we'll tell you about them. The best restaurants - ask us.\r\nWant to take a break from the city we'll tell you about wilderness canoeing on the Delaware river - just an hour and a half's drive. We can tell you where to find the great salt water fishing with clean beautiful waters just an hour away from the city or how to take a one day trip by bus to ski in Vermont.\r\n\r\n\r\nWHY WILLIAMSBURG?\r\n\r\nWilliamsburg is FABULOUS. It's fast growing and it's fast changing. It's hip. In the 1960's the new and exciting place where culture was blooming was Greenwich Village. In the 70's the SOHO neighborhood was where cheap industrial loft space were being turned into places where the adventurous could move to New York, live cheaply and make the new art, music, and culture. These days Williamsburg has that special chemistry of the New York that's constantly renewing itself.NaNNaN75.0f1.0['email', 'phone', 'reviews', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttWilliamsburgBrooklyn40.70837-73.95352Entire apartmentEntire home/apt31 bathNaN1.0["Refrigerator", "Microwave", "Shampoo", "Air conditioning", "Free street parking", "Kitchen", "Coffee maker", "Oven", "Iron", "Hangers", "Smoke alarm", "Washer", "Dedicated workspace", "Fire extinguisher", "Hot water", "Long term stays allowed", "Extra pillows and blankets", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Dishwasher", "Wifi", "Heating", "Cooking basics", "Stove", "Carbon monoxide alarm"]109.030730043430918162009-05-252020-03-1691.09.010.010.010.09.09.0f1.27
72021-02-06Uptown Sanctuary w/ Private Bath (Month to Month)A charming month-to-month home away from home located in Historic Harlem, Uptown Sanctuary is ideal for lovers of travel, work-life balance, art, soulful living, and culture.<br /><br /><b>The space</b><br />Cozy, bedroom with private bathroom with its own ensuite bathroom available in a furnished 2B/2B co-op with hardwood floors and a private terrace. Located in an elevator building this unit gets heavenly light and the view from the eighth floor will not disappoint. This sweet Harlem sanctuary is a fifteen-minute train ride from downtown Manhattan and walking distance to transportation making this location close enough to work and a step away from the city buzz when it's time to decompress. 24-hour security guards, laundry and fitness center.<br /><br />This bedroom is ideal for a professional, independent female and sleeps up to three. Weekend, weekday, one-month stays, events, meetings, and regular business travelers in need of a workspace. Be sure to inquire about the special offThis sweet Harlem sanctuary is a 10-20 minute ride from downtown Manhattan, a 20-25 minute ride from Laguardia Airport and is walking distance to transportation making this location a step away from the city buzz when it's time for intimate social relaxation and restoration.2009-05-07A former life in fashion and wellness has left me well traveled and a lover of all things work-life balance and zen living. I have great living chemistry with independent, considerate professional females who don't work from home.NaNNaNNaNf0.0['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'selfie', 'government_id', 'work_email']ttEast HarlemManhattan40.80139-73.94244Private room in condominiumPrivate room11 shared bath1.01.0["Paid parking garage off premises", "Smoke alarm", "Hangers", "Essentials", "Washer", "Dedicated workspace", "Host greets you", "Dryer", "Fire extinguisher", "Heating", "Wifi", "Luggage dropoff allowed", "Elevator", "Hot water", "Free street parking", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]65.03018030609036500NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
82021-02-06UES Beautiful Blue RoomBeautiful peaceful healthy home<br /><br /><b>The space</b><br />Home is fun healthy. <br />Your Night’s Sleep: 100% cotton sheets and a fluffy down comforter.<br />Just pack your favorite comfy shoes and bring your empty suitcases to fill.<br /><br />The Blue room has a twin bed built on the legs of a piano from the 1800's. There is a dresser and a nice size closet for all your clothes. Hairdryer, bedding and towels are provided in your room. The room is sound proof, no street noise, perfect for jet-lag recovery.<br />I feel that if my guests have a good nights sleep, they are full of energy for their adventures, then my guests are happy.<br /><br />The Common Space: approximately 500 square feet, features an Eat-in kitchen, living room and bathroom, to share. There is never more than 2 guests here at a time, this way there is enough space for each of us to get lost in, if we need too.<br /><br />WIFi, and Netflix,<br /><br />The home front is a work of art in constant change.<br /><Location: Five minutes to Central Park, Museum Mile (Guggenheim Museum, Metropolitan Museum, Whitney Museum, The Cooper Hewitt Museum, The Frick Collection and many more. Movie Stars pepper the hood and the area is considered “The New Downtown”. Today’s hipsters moved uptown to escape the over gentrified neighborhoods, such as the LES, the Village and now Chelsea.<br /><br />Shopping: Many cool consignment shops to get your Haute couture, such as the famous Encore.<br /><br />Food: Around the corner, Gourmet Garage, Japanese, French, Mexican, Health food bars, and Joy Burgers<br /><br />Laundry: There is a laundry service on the corner, drop before 10am and pickup after 5pm, washed, dried and folded for $11. You will not miss a beat on your venture and you can still look good.2009-05-12Capturing the Steinbeck side of life in its Fillini moment.\r\nHome is a special place, it is a live-in work of art... A great experience I hope all to enjoy...within an hour100.0100.0f3.0['email', 'phone', 'reviews', 'jumio', 'government_id']ttEast HarlemManhattan40.78962-73.94802Private room in apartmentPrivate room11 shared bath1.01.0["Hair dryer", "Stove", "Breakfast", "Smoke alarm", "Refrigerator", "Host greets you", "Wifi", "Shampoo", "Heating", "Fire extinguisher", "Paid parking off premises", "Free street parking", "Air conditioning", "Hot water", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen", "Coffee maker"]62.03070030609036523302009-10-282019-12-0998.010.010.010.010.010.010.0t1.70
92021-02-05Perfect for Your Parents: Privacy + GardenParents/grandparents coming to town, or are you just here for work or play? You'll love this Victorian townhouse on a quiet residential street. We live on site, and will greet you upon check-in. You'll enjoy your own kitchenette, bedroom, bathroom and living area. There's a huge garden. About 1000 sq ft. in our townhouse. Big hi-def 48-inch TV w/cable and internet, and garden access. NYC short-term-rental compliant!<br /><br /><b>The space</b><br />California King-size bed, en suite bathroom with shower (no tub). Very spacious (for NY) and clean: We follow CDC guidelines for disinfecting. Kitchenette does not have a stove. It features cooktop, microwave, fridge/freezer, sink, cutlery/dishes/pots/pans, coffeepot, teapot as well as coffee, tea. For an oven, you share kitchen one flight up (we don't cook much). Stairs lead to parlor floor. Only two steps to negotiate to enter. Downside: Unit is not particularly sunny.<br /><br /><b>Guest access</b><br />Can access all spaces. Several entResidential, village-like atmosphere. Lots of restaurants. They are unfortunately limited to outdoors and partial indoors during lockdown. Many grocery stores (Wegmans, Trader Joes, Whole Foods). Half block to wonderful Fort Greene Park, and Saturday farmer's market (I like the cinnamon donuts and artisanal bread).2009-05-17I have been an Airbnb host since 2009 -- just a year after it started up. I love tourists and know New York well, having lived here 40 years (Chicago native). Recently retired editor at a major metropolitan newspaper, now a journalism professor at an top Ivy college. Am not a leprechaun.within an hour100.0100.0t1.0['email', 'phone', 'reviews', 'offline_government_id', 'kba', 'selfie', 'government_id', 'identity_manual']ttFort GreeneBrooklyn40.69121-73.97277Entire apartmentEntire home/apt41 bath1.02.0["Single level home", "Refrigerator", "Microwave", "Shampoo", "Air conditioning", "Free street parking", "Kitchen", "Coffee maker", "Iron", "Hangers", "Smoke alarm", "Washer", "Dedicated workspace", "Host greets you", "Dryer", "Fire extinguisher", "Shower gel", "Hot water", "Long term stays allowed", "Extra pillows and blankets", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Cable TV", "Heating", "Patio or balcony", "First aid kit", "Luggage dropoff allowed", "Window guards", "Private entrance", "Garden or backyard", "Carbon monoxide alarm"]199.021125303762337243232010-01-162021-01-2597.010.010.010.010.010.09.0t1.80

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last_scrapednamedescriptionneighborhood_overviewhost_sincehost_abouthost_response_timehost_response_ratehost_acceptance_ratehost_is_superhosthost_total_listings_counthost_verificationshost_has_profile_pichost_identity_verifiedneighbourhood_cleansedneighbourhood_group_cleansedlatitudelongitudeproperty_typeroom_typeaccommodatesbathrooms_textbedroomsbedsamenitiespriceminimum_nightsmaximum_nightsavailability_30availability_60availability_90availability_365number_of_reviewsnumber_of_reviews_ltmfirst_reviewlast_reviewreview_scores_ratingreview_scores_accuracyreview_scores_cleanlinessreview_scores_checkinreview_scores_communicationreview_scores_locationreview_scores_valueinstant_bookablereviews_per_month
370022021-02-05A+ Location City Studio (Queen & Twin Bed)NaNNaN2020-06-03We are delighted to accommodate you during your stay. We are passionate about providing the finest possible service, and we are providing accommodations within a very residential setting - whether for vacation, business or extended stay.\nwithin an hour100.099.0f38.0['email', 'phone', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttMidtownManhattan40.747453-73.988046Entire apartmentEntire home/apt31 bathNaN2.0["Refrigerator", "Microwave", "Shampoo", "Air conditioning", "Kitchen", "Coffee maker", "Oven", "Iron", "Hangers", "Washer", "Dedicated workspace", "Dryer", "Fire extinguisher", "Shower gel", "Hot water", "Long term stays allowed", "Hair dryer", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Heating", "Cooking basics", "Stove", "Luggage dropoff allowed", "Conditioner"]126.011125028585800NaTNaTNaNNaNNaNNaNNaNNaNNaNtNaN
370032021-02-06Cozy living room is available for stayA comfortable and cozy place, with a SUPER close train station to NYC (25-35 to Manhattan). Easy access to shopping malls from NJ and NYC, free parking location in the facility . Grocery store, hospital and pharmacy conveniently located at a walking distance. This place has the advantage of calm and quiet of Astoria but a SUPER , FAST and EASY access to the big apple NYC. You won't find such a bargain anywhere in our expensives cities.NaN2019-11-30NaNwithin an hour100.0NaNf1.0['email', 'phone', 'offline_government_id', 'selfie', 'government_id']ttAstoriaQueens40.763440-73.917130Private room in earth housePrivate room22 baths2.02.0["Hair dryer", "Iron", "Hangers", "Essentials", "Smoke alarm", "TV", "Wifi", "Heating", "Hot water", "Air conditioning", "Kitchen"]85.01724548435900NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
370042021-02-06Private room with a private bathroom in Astoria !A comfortable and cozy place, with a SUPER close train station to NYC (25-35 min to Manhattan). Easy access to shopping places from the city, street parking available . Grocery stores, hospital and pharmacy conveniently located at a walking distance. This place has the advantage of Astoria of Queens,NY but a SUPER , FAST and EASY access to the big apple NYC. You won't find such a bargain anywhere in our expensives cities.<br /><br /><b>The space</b><br />Great space available for everyone. The unique decor of kitchen and the ambiance in the house would definitely provides the quests comfort, and peace..<br /><br /><b>Guest access</b><br />You will be able to access living room, bathroom and kitchen as well as closets etc as you need.NaN2019-11-30NaNwithin an hour100.0NaNf1.0['email', 'phone', 'offline_government_id', 'selfie', 'government_id']ttAstoriaQueens40.763690-73.916680Private room in earth housePrivate room22 baths2.02.0["Hair dryer", "Iron", "Hangers", "Essentials", "Smoke alarm", "TV", "Host greets you", "Wifi", "Heating", "Hot water", "Air conditioning", "Long term stays allowed", "Kitchen"]72.032925558536000NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
370052021-02-05Spacious Modern 2 bedrooms close to transportationNaNNaN2015-12-05I am an adventurer, I love to travel around the world. I have already been to about 25 countries and counting. I am fascinated with different cultures and mother nature's wonders. My favorite travel destination thus far is Barcelona for the many world heritage sites they have. Having to host other world travelers gives me pleasure in helping them achieve part of their goals. Just like when I travel abroad. Lets continue to make journeys around the world. \r\n\r\nwithin a few hours90.088.0t11.0['email', 'phone', 'facebook', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttBedford-StuyvesantBrooklyn40.678600-73.911100Entire apartmentEntire home/apt41 bath2.02.0["First aid kit", "Hair dryer", "Iron", "Hangers", "Essentials", "Washer", "TV", "Smoke alarm", "Dryer", "Shampoo", "Heating", "Fire extinguisher", "Dedicated workspace", "Wifi", "Private entrance", "Hot water", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]80.030365000000NaTNaTNaNNaNNaNNaNNaNNaNNaNtNaN
370062021-02-05Beautiful & Cosy 1 Bedroom apartmentLovely and clean apartment for a perfect stay in the city. <br />It is a 1 bedroom apartment with view on the East side river. <br />Very calm as you are on the 35th floor. <br />Kitchen has all the utilities if you want to cook. <br />Bathroom has a toilet, bath and separate sink. <br /><br />Please reach out if you have any questions !Financial district with walking distance all the subways.2017-08-16Love discovering new places!NaNNaNNaNf1.0['phone', 'offline_government_id', 'government_id']ttFinancial DistrictManhattan40.705080-74.008680Entire apartmentEntire home/apt41 bath1.01.0["First aid kit", "Hair dryer", "Iron", "Hangers", "Essentials", "Smoke alarm", "TV", "Gym", "Dryer", "Shampoo", "Heating", "Wifi", "Private entrance", "Elevator", "Hot water", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]103.02301717171700NaTNaTNaNNaNNaNNaNNaNNaNNaNtNaN
370072021-02-06Cozy One-Bedroom with Full Kitchen Near ManhattanNaNNaN2019-03-27NaNwithin an hour100.0100.0f2.0['phone', 'offline_government_id', 'government_id']ttWoodsideQueens40.744150-73.909410Entire apartmentEntire home/apt31 bath1.01.0["Hair dryer", "Smoke alarm", "Essentials", "TV", "Dedicated workspace", "Wifi", "Shampoo", "Heating", "Private entrance", "Hot water", "Air conditioning", "Long term stays allowed", "Carbon monoxide alarm", "Kitchen"]90.03112530609036500NaTNaTNaNNaNNaNNaNNaNNaNNaNtNaN
370082021-02-06Grand Concourse GemNaNNaN2019-08-21Native New Yorker\nEclectic dabbler (writer, painter, cook)\nType A-NaNNaN0.0f1.0['email', 'phone', 'offline_government_id', 'government_id']ttNorwoodBronx40.875750-73.883990Private room in apartmentPrivate room11 shared bath1.00.0["Refrigerator", "Single level home", "Microwave", "Shampoo", "Dining table", "Air conditioning", "Wine glasses", "Baking sheet", "Free street parking", "Bathtub", "Kitchen", "Coffee maker", "Oven", "Rice maker", "Iron", "Hangers", "Smoke alarm", "Washer", "Dedicated workspace", "Dryer", "Fire extinguisher", "Shower gel", "Hot water", "Cleaning products", "Long term stays allowed", "Body soap", "Paid parking on premises", "Extra pillows and blankets", "Hair dryer", "Bed linens", "Room-darkening shades", "Essentials", "Dishes and silverware", "TV", "Dishwasher", "Lock on bedroom door", "Wifi", "Heating", "Safe", "Clothing storage", "Cooking basics", "First aid kit", "Stove", "Freezer", "Sound system", "Luggage dropoff allowed", "Toaster", "Laundromat nearby", "Conditioner", "Carbon monoxide alarm"]520.0136515457229200NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
370092021-02-06Natural Light-Filled Home in Upper East SidePrivate room with Queen bed in a 4 bedroom, 4 bathroom home.<br /><br />Move-in within first 14 days of availability required<br /><br /><b>The space</b><br />Fully furnished private room in a 4 bedroom, 4 bathroom shared home in Upper East Side. Flexible 1-18 month lease, no broker or extra fees.<br /><br />About This Room<br /><br />A room of one's own, featuring everything you need for a good night's sleep. Anything else that tickles your fancy, too. Comes with a generously-sized bed, desk, ambient lighting and somewhere fancy to hang your clothes.<br /><br />About This Home<br /><br />This furnished 4 bedroom 4 bathroom apartment is located in the exclusive Upper East Side neighborhood of New York City. This unit has been designed to create a bespoke NYC experience. From the newly renovated kitchen to the in-unit laundry, every detail ensures a true turnkey move-in.<br /><br />Entering the unit through the balanced neutral cream color kitchen area. The breakfast nook is in the centWelcome to The Upper East Side – located northeast of Manhattan and one of the most elevated neighborhoods in New York. The Upper East Side is a family-oriented and quiet neighborhood. Known for its upscale real estate, private schools and it's slow, relaxed vibe – especially compared to busier districts of NYC. Spend your weekends with a stroll through neighboring Central Park or along the streets dotted with designer boutiques and bakeries.<br /><br />The Upper East Side also is rich in art and culture. The many museums draw out crowds of art enthusiasts, especially The Metropolitan Museum of Art, which has over 5,000 years' worth of art from around the globe. For foodies, the neighborhood is filled with trendy restaurants, and cafes, which are known for creating the most Instagrammable dishes—the world famous cupcake ATM was founded right here, on Lexington Avenue. It also lives up to the hype of being a top shopping spot. From Louis Vuitton to Prada, and even Nine West and H&M, all2019-10-29At June Homes, our mission is to make renting an apartment as easy and stress-free as possible. We make applying simple and seamless, charge no hidden fees, and take care of the little things. All of our homes are fully furnished, and include Netflix/HBO, monthly delivery of home supplies, WiFi and utilities for $125-$200/month. If you have any issues, we’re available with 24-hour support.\nAll of our apartments are available with flexible terms, meaning you can lease for 1–18 months. New to the city? Consider moving in for two months and then trying out a new neighborhood. Need a roommate? We also offer shared homes to our member-only community. Our design team ensures that each home meets our elevated standards, and you can select between furnished or unfurnished. It’s your call. It’s your home.within an hour100.053.0f1.0['email', 'phone', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttMidtownManhattan40.757740-73.961730Private room in apartmentPrivate room11 shared bath1.01.0["Refrigerator", "Microwave", "Dining table", "Air conditioning", "Kitchen", "Keypad", "Oven", "Smoke alarm", "Hangers", "Washer", "Dedicated workspace", "Dryer", "Hot water", "Cleaning products", "Long term stays allowed", "Hot water kettle", "Extra pillows and blankets", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Dishwasher", "Wifi", "Heating", "Pocket wifi", "Cooking basics", "Stove", "Freezer", "Carbon monoxide alarm"]63.03090111100NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
370102021-02-05Spacious Living in the Heart of Upper East SidePrivate room with Queen bed in a 2 bedroom, 1 bathroom home.<br /><br />Move-in within first 14 days of availability required<br /><br /><b>The space</b><br />Fully furnished private room in a 2 bedroom, 1 bathroom shared home in Upper East Side. Flexible 1-18 month lease, no broker or extra fees.<br /><br />About This Room<br /><br />Colorful and bright, this queen bedroom is dressed up and ready for you with all the gems required for easy, tasteful living. Unpack your suitcase into a full height closet with overhead storage and then kick up your feet and relax on the Mid-century tufted bed fitted with luxe linens and hand selected cozy accessories.<br /><br />About This Home<br /><br />This perfectly sized 2 bedroom 1 bathroom flat, located in the Upper East Side neighborhood of New York City, is fully designed for a grande New York City living experience. From the open kitchen to the cozy bedrooms, you’ll surely be happy to call this home.<br /><br />As you enter you’ll long hallwayWelcome to The Upper East Side – located northeast of Manhattan and one of the most elevated neighborhoods in New York. The Upper East Side is a family-oriented and quiet neighborhood. Known for its upscale real estate, private schools and it's slow, relaxed vibe – especially compared to busier districts of NYC. Spend your weekends with a stroll through neighboring Central Park or along the streets dotted with designer boutiques and bakeries.<br /><br />The Upper East Side also is rich in art and culture. The many museums draw out crowds of art enthusiasts, especially The Metropolitan Museum of Art, which has over 5,000 years' worth of art from around the globe. For foodies, the neighborhood is filled with trendy restaurants, and cafes, which are known for creating the most Instagrammable dishes—the world famous cupcake ATM was founded right here, on Lexington Avenue. It also lives up to the hype of being a top shopping spot. From Louis Vuitton to Prada, and even Nine West and H&M, all2019-10-29At June Homes, our mission is to make renting an apartment as easy and stress-free as possible. We make applying simple and seamless, charge no hidden fees, and take care of the little things. All of our homes are fully furnished, and include Netflix/HBO, monthly delivery of home supplies, WiFi and utilities for $125-$200/month. If you have any issues, we’re available with 24-hour support.\nAll of our apartments are available with flexible terms, meaning you can lease for 1–18 months. New to the city? Consider moving in for two months and then trying out a new neighborhood. Need a roommate? We also offer shared homes to our member-only community. Our design team ensures that each home meets our elevated standards, and you can select between furnished or unfurnished. It’s your call. It’s your home.within an hour100.053.0f1.0['email', 'phone', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttUpper East SideManhattan40.762420-73.959660Private room in apartmentPrivate room11 shared bath1.01.0["Refrigerator", "Dining table", "Air conditioning", "Kitchen", "Oven", "Smoke alarm", "Hangers", "Dedicated workspace", "Cleaning products", "Long term stays allowed", "Hot water kettle", "Extra pillows and blankets", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Wifi", "Heating", "Pocket wifi", "Cooking basics", "Freezer", "Stove", "Toaster", "Laundromat nearby", "Carbon monoxide alarm"]67.0309025558536000NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN
370112021-02-05Find Cozy in this Upper West Side Furnished HomePrivate room with Queen bed in a 3 bedroom, 2 bathroom home.<br /><br />Move-in within first 14 days of availability required<br /><br /><b>The space</b><br />Fully furnished private room in a 3 bedroom, 2 bathroom shared home in Upper West Side. Flexible 1-18 month lease, no broker or extra fees.<br /><br />About This Room<br /><br />Ready your boss on speed-dial, because this is a room that is nearly impossible to tear away from. Featuring modern funishings with a mid-centuary beat; all you need to bring is your favorite fiddle leaf and whatever outfits you are planning to wear on that date before you cancel.<br /><br />About This Home<br /><br />This Upper West Side 3-bedroom, 2-bathroom apartment features exposed brick walls, a spacious kitchen, and an in-unit washer & dryer. Situated off the northwest corner of Central Park, you're never too far from an outdoor stroll.<br /><br />The home gets a lot of natural light and showcases a warm color palette with wood furniture accents, cNaN2019-10-29At June Homes, our mission is to make renting an apartment as easy and stress-free as possible. We make applying simple and seamless, charge no hidden fees, and take care of the little things. All of our homes are fully furnished, and include Netflix/HBO, monthly delivery of home supplies, WiFi and utilities for $125-$200/month. If you have any issues, we’re available with 24-hour support.\nAll of our apartments are available with flexible terms, meaning you can lease for 1–18 months. New to the city? Consider moving in for two months and then trying out a new neighborhood. Need a roommate? We also offer shared homes to our member-only community. Our design team ensures that each home meets our elevated standards, and you can select between furnished or unfurnished. It’s your call. It’s your home.within an hour100.053.0f1.0['email', 'phone', 'jumio', 'offline_government_id', 'selfie', 'government_id', 'identity_manual']ttUpper West SideManhattan40.798500-73.962160Private room in apartmentPrivate room11 shared bath1.01.0["Refrigerator", "Microwave", "Air conditioning", "Kitchen", "Keypad", "Oven", "Smoke alarm", "Hangers", "Washer", "Dedicated workspace", "Dryer", "Cleaning products", "Long term stays allowed", "Hot water kettle", "Extra pillows and blankets", "Bed linens", "Essentials", "Dishes and silverware", "TV", "Dishwasher", "Wifi", "Heating", "Pocket wifi", "Cooking basics", "Stove", "Freezer", "Toaster", "Laundromat nearby", "Carbon monoxide alarm"]66.0309018487835300NaTNaTNaNNaNNaNNaNNaNNaNNaNfNaN